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Dual template using P123-gelatin for synthesized large mesoporous silica for enhanced adsorption of dyes

South African Journal of Chemical engineering 2023年 43卷 312-326页

作者： Safitri, Widiya Nur Habiddin, Habiddin Ulfa, Maria Trisunaryanti, Wega Bahruji, Hasliza Holilah, Holilah Rohmah, Alya Awinatul Sholeha, Novia Amalia Jalil, Aishah Abdul Santoso, Eko Prasetyoko, Didik Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember East Java Keputih Sukolilo Surabaya 60111 Indonesia Chemistry Education Study Program Faculty of Teacher Training and Education Universitas Sebelas Maret Jl. Ir. Sutami 36A Surakarta 57126 Indonesia Department of Chemistry Faculty of Science Universitas Gadjah Mada Sekip Utara Sleman Indonesia Centre for Advanced Material and Energy Sciences Universiti Brunei Darussalam Bandar Seri Begawan BE 1410 Brunei Darussalam Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Cibinong 16911 Indonesia Department of Food Science and Technology Faculty of Agriculture Halu Oleo University Indonesia College of Vocational Studies Bogor Agricultural University (IPB University) Jalan Kumbang No. 14 Bogor 16151 Indonesia Department of Chemical Engineering Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia 81310 UTM Johor Skudai Johor Bahru Malaysia

Mesoporous Silica with a large mesopore channel was synthesized using the sol-gel method for dye adsorption. A dual template consisting of P123 and gelatin at different ratios was employed in the sol-gel synthesis to enhance surface area and mesopore diameter. Gelatin is a green pore directing agent that strengthens P123 thermal stability during the calcination of silicate gel. Optimization of P123:gelatin ratio to 1:0.02 increased the surface area of mesoporous silica to 561.9 m²/g and expanded the pore diameter to 10 nm. The large pore diameter and surface area enhanced methylene blue adsorption capacity to 363.63 mg/g. The adsorption of methylene blue on mesoporous silica follows the pseudo second-order kinetic and the Langmuir model. Regeneration studies using thermal and chemical treatments exhibited the potential of mesoporous silica as an adsorbent for multiple adsorption-desorption of dyes. © 2022 The Author(s)

关键词： Dual template Dye Gelatin Mesoporous silica Pluronic P123

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Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma

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Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 329-342页

作者： Hailin Li Weiyuan Huang Siwen Wang Priya SBalasubramanian Gang Wu Mengjie Fang Xuebin Xie Jie Zhang Di Dong Jie Tian Feng Chen Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang UniversityBeijing 100191China CAS Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Radiology Hainan General Hospital(Hainan Affiliated Hospital of Hainan Medical University)HaikouHainan 570311China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Psychiatry Weill Cornell MedicineNew YorkNY 10065USA Department of Radiotherapy Hainan General Hospital(Hainan Affiliated Hospital of Hainan Medical University)HaikouHainan 570311China Department of Radiology Kiang Wu HospitalSanto AntónioMacao 999078China Department of Radiology Zhuhai People’s Hospital(Zhuhai Hospital Affiliated With Jinan University)ZhuhaiGuangdong 519000China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi’anShaanxi 710126China Zhuhai Precision Medical Center Zhuhai People’s HospitalZhuhaiGuangdong 519000China.

Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to investigate the role of DCR-MR in predicting progression-free survival (PFS) in patients with NPC using magnetic resonance (MR)- and DCE-MR-based radiomic models. A total of 434 patients with two MR scanning sequences were included. The MR- and DCE-MR-based radiomics models were developed based on 289 patients with only MR scanning sequences and 145 patients with four additional pharmacokinetic parameters (volume fraction of extravascular extracellular space (ve), volume fraction of plasma space (vp), volume transfer constant (Ktrans), and reverse reflux rate constant (kep) of DCE-MR. A combined model integrating MR and DCE-MR was constructed. Utilizing methods such as correlation analysis, least absolute shrinkage and selection operator regression, and multivariate Cox proportional hazards regression, we built the radiomics models. Finally, we calculated the net reclassification index and C-index to evaluate and compare the prognostic performance of the radiomics models. Kaplan-Meier survival curve analysis was performed to investigate the model’s ability to stratify risk in patients with NPC. The integration of MR and DCE-MR radiomic features significantly enhanced prognostic prediction performance compared to MR- and DCE-MR-based models, evidenced by a test set C-index of 0.808 vs 0.729 and 0.731, respectively. The combined radiomics model improved net reclassification by 22.9%-52.6% and could significantly stratify the risk levels of patients with NPC (p = 0.036). Furthermore, the MR-based radiomic feature maps achieved similar results to the DCE-MR pharmacokinetic parameters in terms of reflecting the underlying angiogenesis information in NPC. Compared to conventional MR-based radiomics models, the combined radiomics model integrating MR and DCE-MR showed

关键词： Dynamic contrast-enhanced magnetic resonance imaging Magnetic resonance imaging Radiomics Prognostic prediction

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False data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

False Data Injection Attack on Atmospheric Electric Field in...

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2022 International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2022

作者： Li, Xiang Hayawi, Kadhim Chen, Yi Chang, Shih Yu Wen, Hong Ho, Pin-Han Yang, Ling Yin, Qiyuan College of Electronic Engineering Chengdu University of Information Technology Chengdu610225 China College of Technological Innovation Zayed University Abu Dhabi144534 United Arab Emirates School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Cma Key Laboratory of Atmospheric Sounding Chengdu610225 China San Jose State University Department of Applied Data Science San JoseCA95192 United States University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada Guangdong Meteorological Public Safety Technical Support Center Guangzhou510640 China

ISBN: (数字)9781665470209

ISBN: (纸本)9781665470209

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False data Injection Attack (FDIA). However, there is a lack of research on False data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning. © 2022 IEEE.

关键词： Principal component analysis

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Recent trend of metal promoter role for CO₂ hydrogenation to C₁ and C₂₊ products

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South African Journal of Chemical engineering 2023年 44卷 14-30页

作者： Sholeha, Novia Amalia Holilah, Holilah Bahruji, Hasliza Ayub, Athirah Widiastuti, Nurul Ediati, Ratna Jalil, Aishah Abdul Ulfa, Maria Masruchin, Nanang Nugraha, Reva Edra Prasetyoko, Didik College of Vocational Studies Bogor Agricultural University (IPB University) Jalan Kumbang No. 14 Bogor 16151 Indonesia Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Cibinong 16911 Indonesia Department Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Keputih Surabaya Sukolilo 60111 Indonesia Centre of Advanced Material and Energy Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei Darussalam Department of Chemical Engineering Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Johor Bahru Malaysia Centre of Hydrogen Energy Institute of Future Energy Universiti Teknologi Malaysia Skudai 81310 UTM Skudai Johor Johor Bahru Malaysia Chemistry Education Study Program Faculty of Teacher Training and Education Sebelas Maret University Jl. Ir. Sutami 36A Surakarta 57126 Indonesia Research Collaboration Center for Biomass and Biorefinery between BRIN and Universitas Padjadjaran Jatinangor 45363 Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Pembangunan Nasional “Veteran” Jawa Timur East Java Surabaya 60294 Indonesia

CO2 hydrogenation as sustainable route for generation of value-added carbon feedstock is identified as green pathway for mitigation of greenhouse gasses emission. CO2 methanation is one of the promising solutions, whi... 详细信息

CO₂ hydrogenation as sustainable route for generation of value-added carbon feedstock is identified as green pathway for mitigation of greenhouse gasses emission. CO₂ methanation is one of the promising solutions, which only requires reactions at atmospheric pressure while utilizing metal catalysts to overcome kinetic limitations. Metal catalysts can be promoted to alter reducibities, CO₂ adsorption capacities, and H_2[sbnd]CO₂ dissociation potential. The role of metal promoter such as rare earth elements (Ce, Mn, Co, and La) and alkali and alkali earth metal (Li, Na, Ca, and K) will be discussed within the scope of CO₂ methanation. The aspect of catalysts modification towards hydrogen dissociation potential and surface oxygen vacancy will be emphasized to enhance selectivity for methane. Another pathway for CO₂ hydrogenation is via further conversion into longer chain molecules such as olefin and ethanol. The benefit of metal promoter will be discussed in this review on the effect towards promoting C[sbnd]C coupling reaction for producing longer chain alcohol and light olefin. The strategies to develop active catalysts for the coupling reaction of C[sbnd]C will be emphasized with the promoter introduction. For the hydrogenation of CO₂ to longer chain molecules, the main metal catalysts Ni, Pd, Rh, and Co, and their modification with promoter such as Ga, Cu, and alkali metal Na, K will be discussed. A critical analysis of the CO₂ methanation mechanism and further C[sbnd]C reaction to longer chain molecules will be discussed, particularly the effect of metal promoters to stabilize the intermediate and maneuver the catalytic reaction pathway into the desired products. © 2023 The Author(s)

关键词： C1 products C2+ products CO2 Hydrogenation Metal promoter

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The Nord Stream pipeline gas leaks released approximately 220,000 tonnes of methane into the atmosphere

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Environmental science and Ecotechnology 2022年第4期12卷 3-7页

作者： Mengwei Jia Fei Li Yuzhong Zhang Mousong Wu Yingsong Li Shuzhuang Feng Hengmao Wang Huilin Chen Weimin Ju Jun Lin Jianwei Cai Yongguang Zhang Fei Jiang Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjingJiangsu Province210023China Key Laboratory of Coastal Environment and Resources of Zhejiang Province School of EngineeringWestlake UniversityHangzhouZhejiang Province310030China Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric SciencesNanjing UniversityNanjingJiangsu Province210023China China Centre for Resources Satellite Data and Application Beijing100094China International Joint Carbon Neutrality Laboratory NanjingJiangsu Province210023China Nantong Academy of Intelligent Sensing NantongJiangsu Province226000China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application NanjingJiangsu Province210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjingJiangsu Province210023China

Sudden mega natural gas leaks of two Nord Stream pipelines in the Baltic Sea(Denmark)occurred from late September to early October 2022,releasing large amounts of methane into the *** inferred the methane emissions of this event based on surface in situ observations using two inversion methods and two meteorological reanalysis datasets,supplemented with satellite-based *** conclude that approximately 220±30 Gg of methane was released from September 26 to October 1,2022.

关键词： methane approximate conclude

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Identification of Clinical Features Associated with Mortality in COVID-19 Patients

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Operations Research Forum 2023年第1期4卷 16页

作者： Eskandarian, Rahimeh Alizadehsani, Roohallah Behjati, Mohaddeseh Zahmatkesh, Mehrdad Sani, Zahra Alizadeh Haddadi, Azadeh Kakhi, Kourosh Roshanzamir, Mohamad Shoeibi, Afshin Hussain, Sadiq Khozeimeh, Fahime Darbandy, Mohammad Tayarani Joloudari, Javad Hassannataj Lashgari, Reza Khosravi, Abbas Nahavandi, Saeid Islam, Sheikh Mohammed Shariful Internal Medicine Research Center Semnan University of Medical Sciences Semnan Iran Institute for Intelligent Systems Research and Innovation (IISRI) Deakin University Victoria Australia Rajaei Cardiovascular Medical and Research Center Iran University of Medical Sciences Tehran Iran Omid Hospital Iran University of Medical Sciences Tehran Iran Department of Biology Faculty of Basic Sciences Shahrekord Branch Islamic Azad University Shahrekord Iran Department of Computer Engineering Faculty of Engineering Fasa University Fasa 74617-81189 Iran Data Science and Computational Intelligence Institute University of Granada Granada Spain System Administrator Dibrugarh University Assam 786004 India School of Architecture Islamic Azad University Taft Taft *** Iran Department of Computer Engineering Faculty of Engineering University of Birjand Birjand Iran Department of Computer Engineering Amol Institute of Higher Education Amol Iran Institute of Medical Science and Technology Shahid Beheshti University Tehran Iran School of Engineering and Applied Sciences Harvard Paulson Harvard University Allston 02134 MA United States Institute for Physical Activity and Nutrition School of Exercise and Nutrition Sciences Deakin University Geelong 3220 VIC Australia Cardiovascular Division The George Institute for Global Health Newtown Australia Sydney Medical School University of Sydney Camperdown Australia

Understanding clinical features and risk factors associated with COVID-19 mortality is needed to early identify critically ill patients, initiate treatments and prevent mortality. A retrospective study on COVID-19 patients referred to a tertiary hospital in Iran between March and November 2020 was conducted. COVID-19-related mortality and its association with clinical features including headache, chest pain, symptoms on computerized tomography (CT), hospitalization, time to infection, history of neurological disorders, having a single or multiple risk factors, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia were investigated. Based on the investigation outcome, decision tree and dimension reduction algorithms were used to identify the aforementioned risk factors. Of the 3008 patients (mean age 59.3 ± 18.7 years, 44% women) with COVID-19, 373 died. There was a significant association between COVID-19 mortality and old age, headache, chest pain, low respiratory rate, oxygen saturation < 93%, need for a mechanical ventilator, having symptoms on CT, hospitalization, time to infection, neurological disorders, cardiovascular diseases and having a risk factor or multiple risk factors. In contrast, there was no significant association between mortality and gender, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Our results might help identify early symptoms related to COVID-19 and better manage patients according to the extracted decision tree. The proposed ML models identified a number of clinical features and risk factors associated with mortality in COVID-19 patients. These models if implemented in a clinical setting might help to early identify patients needing medical attention and care. However, more studies are needed to confirm these findings. © 2023, The Author(s).

关键词： COVID‐19 Machine learning Mortality Risk factors Symptoms

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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Revocable and certificateless public auditing for cloud storage

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science China(Information sciences) 2020年第10期63卷 282-284页

作者： Yinghui ZHANG Tiantian ZHANG Shengmin XU Guowen XU Dong ZHENG School of Cyberspace Security Xi'an University of Posts and Telecommunications Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology National Engineering Laboratory for Wireless Security Xi'an University of Posts and Telecommunications Secure Mobile Centre School of Information SystemsSingapore Management University School of Computer Science and Engineering University of Electronic Science and Technology of China

Dear editor,Plenty of computing and storage resources in the cloud are provided for users with restricted computing and storage resources,which has attracted the attention of many researchers[1,2].A generic blockchain-based cloud data auditing scheme[3] is proposed,which is compatible with any blockchains including the bitcoin *** the data integrity checking scheme,certificate-

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All-fiber-transmission photometry for simultaneous optogenetic stimulation and multi-color neuronal activity recording

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Opto-Electronic Advances 2022年第12期5卷 20-34,F0004页

作者： Zhongyang Qi Qingchun Guo Shu Wang Mingyue Jia Xinwei Gao Minmin Luo Ling Fu Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China MoE Key Laboratory for Biomedical Photonics School of Engineering SciencesHuazhong University of Science and TechnologyWuhan 430074China National Institute of Biological Sciences Beijing 102206China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing 100191China School of Biomedical Engineering Capital Medical UniversityBeijing 100069China Chinese Institute for Brain Research Beijing 102206China School of Life Sciences Tsinghua UniversityBeijing 100084China

Manipulating and real-time monitoring of neuronal activities with cell-type specificity and precise spatiotemporal resolution during animal behavior are fundamental technologies for exploring the functional connectivity, information transmission, and physiological functions of neural circuits in vivo. However, current techniques for optogenetic stimulation and neuronal activity recording mostly operate independently. Here, we report an all-fiber-transmission photometry system for simultaneous optogenetic manipulation and multi-color recording of neuronal activities and the neurotransmitter release in a freely moving animal. We have designed and manufactured a wavelength-independent multi-branch fiber bundle to enable simultaneous optogenetic manipulation and multi-color recording at different wavelengths. Further, we combine a laser of narrow linewidth with the lock-in amplification method to suppress the optogenetic stimulation-induced artifacts and channel crosstalk. We show that the collection efficiency of our system outperforms a traditional epi-fluorescence system. Further, we demonstrate successful recording of dynamic dopamine(DA) responses to unexpected rewards in the nucleus accumbens(NAc) in a freely moving mouse. We also show simultaneous dual-color recording of neuronal Ca2+ signals and DA dynamics in the NAc upon delivering an unexpected reward and the simultaneous optogenetic activating at dopaminergic terminals in the same location. Thus, our multi-function fiber photometry system provides a compatible, efficient, and flexible solution for neuroscientists to study neural circuits and neurological diseases.

关键词： fiber photometry all-fiber-transmission multi-color optogenetic neuroscience

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Penetration trajectory optimization for the hypersonic gliding vehicle encountering two interceptors

arXiv

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arXiv 2022年

作者： Shen, Zhipeng Yu, Jianglong Dong, Xiwang Hua, Yongzhao Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

The penetration trajectory optimization problem for the hypersonic gliding vehicle (HGV) encountering two interceptors is investigated. The HGV penetration trajectory optimization problem considering the terminal target area is formulated as a nonconvex optimal control problem. The nonconvex optimal control problem is transformed into a second-order cone programming (SOCP) problem, which can be solved by state-of-the-art interior-point methods. In addition, a penetration strategy that only requires the initial line-of-sight angle information of the interceptors is proposed. The convergent trajectory obtained by the proposed method allows the HGV to evade two interceptors and reach the target area successfully. Furthermore, a successive SOCP method with a variable trust region is presented, which is critical to balancing the trade-off between time consumption and optimality. Finally, the effectiveness and performance of the proposed method are verified by numerical simulations. Copyright © 2022, The Authors. All rights reserved.

关键词： Numerical methods

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