Asian Journal of Civil Engineering最新文献_第10页

Hybrid metaheuristic optimization algorithm for prediction of fatigue life performance of fiber-reinforced concrete 纤维增强混凝土疲劳寿命预测的混合元启发式优化算法

Asian Journal of Civil Engineering Pub Date : 2025-05-30 DOI: 10.1007/s42107-025-01370-3

Hirkani Padwad, Nischal Puri, Sneha A. Sahare, Ashwini C. Gote, Tejas R. Patil, Niteen T. Kakade

{"title":"Hybrid metaheuristic optimization algorithm for prediction of fatigue life performance of fiber-reinforced concrete","authors":"Hirkani Padwad, Nischal Puri, Sneha A. Sahare, Ashwini C. Gote, Tejas R. Patil, Niteen T. Kakade","doi":"10.1007/s42107-025-01370-3","DOIUrl":"10.1007/s42107-025-01370-3","url":null,"abstract":"<div><p>This paper deals with an integrated and multi-scale hybrid intelligence framework for optimizing fiber orientation, improving crack control, and predicting the fatigue life of FRC. At the core of such model construction is a hybrid evolutionary-physics informed neural network (HE-PINN), which employs evolutionary optimization and physics Informed learning to refine fiber orientation on the basis of outcome material properties and cyclic loading parameters in process, thus ensuring physical prediction of fiber-matrix interaction under stress redistribution. Along with this construction, the adaptive fractal dimension based metaheuristic is introduced to understand and monitor real-time image-based crack evolution in real-time; this will use fractal geometry to control the microcrack growth toward localization while dissipating energy within concrete-satisfied limits. the stress wave propagation-based adaptive swarm optimization (SWP-ASO) constructs a fusion of wavelet-transformed stress features that come from finite element simulations for load redistribution optimization function of fiber placements. It thus advances a data-driven generative designing scheme eliminating the human bias and training itself to learn high-performance reinforcement layouts through the generative adversarial network for fiber network optimization (GAN-FNO). Finally, an adaptive Bayesian-Gaussian process regression (AB-GPR) module provides real-time fatigue life prediction with uncertainty quantification and an adaptive-learning process. This combined architecture therefore provides an improvement of between 30 and 40% in fatigue life, an increase of up to 50% in energy absorption, and a reduction of up to 35% in the rates of crack propagation, presenting a considerable advancement in predictive and prescriptive modeling of smart FRC designs.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3245 - 3256"},"PeriodicalIF":0.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145171780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An intelligent approach for optimizing sugarcane transporting cost and logistics management 甘蔗运输成本优化与物流管理的智能方法

Asian Journal of Civil Engineering Pub Date : 2025-05-30 DOI: 10.1007/s42107-025-01362-3

Radha Halagani, Bhimasen Soragaon, S. M. Rajesh, V. N. Shailaja

{"title":"An intelligent approach for optimizing sugarcane transporting cost and logistics management","authors":"Radha Halagani, Bhimasen Soragaon, S. M. Rajesh, V. N. Shailaja","doi":"10.1007/s42107-025-01362-3","DOIUrl":"10.1007/s42107-025-01362-3","url":null,"abstract":"<div><p>Sugarcane transportation is one of the significant expenses of sugar production. This paper addresses sugarcane transportation costs and logistics systems to offer the mill a proper quality and quantity of sugarcane. This study aimed to optimize transportation costs and sugarcane quality to produce at the mill. A new approach, Lyrebird-based Sequence Neural Network (LbSNN), is proposed to focus specifically on optimizing transportation costs and logistics management. It involves a pre-processing function to filter out noisy data to ensure cleaner and more reliable input for further analysis. The Lyrebird optimization method is then used to perform a feature analysis, which efficiently allows the selection of the most relevant features from the dataset to improve decision-making accuracy. Consequently, the sequence neural network is designed to optimize transportation costs and ease the process of logistics management. The efficacy of the suggested approach is assessed using several performance criteria, including recall 99.9%, precision 99.9%, accuracy 99.9%, f-score 99.9% and error rate 0.1%. The outcomes demonstrate that the proposed technique effectively handles logistics and transportation problems.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3197 - 3210"},"PeriodicalIF":0.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145171778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review on utilization of electronic waste in construction industry as binder, mortar and concrete 电子垃圾在建筑行业中作为粘结剂、砂浆和混凝土的利用综述

Asian Journal of Civil Engineering Pub Date : 2025-05-28 DOI: 10.1007/s42107-025-01373-0

Alagar Karthick, Arunkumar Priya

引用次数: 0

Comprehensive review on predicting CBR values using machine learning techniques 使用机器学习技术预测CBR值的综合综述

Asian Journal of Civil Engineering Pub Date : 2025-05-27 DOI: 10.1007/s42107-025-01369-w

Adel Hassan Yahya Habal, Amal Medjnoun, Lynda Djerbal, Ramdane Bahar

{"title":"Comprehensive review on predicting CBR values using machine learning techniques","authors":"Adel Hassan Yahya Habal, Amal Medjnoun, Lynda Djerbal, Ramdane Bahar","doi":"10.1007/s42107-025-01369-w","DOIUrl":"10.1007/s42107-025-01369-w","url":null,"abstract":"<div><p>Evaluating the subgrade bearing capacity using the California bearing ratio test is necessary in infrastructure projects. The California Bearing Ratio (CBR) is a critical parameter in geotechnical engineering, particularly in the design of pavements and subgrade materials. Traditional methods for predicting CBR, such as empirical correlations and laboratory tests, are often time-consuming, labor-intensive, and limited in capturing complex interactions between soil properties and external factors. Machine learning (ML) has emerged as a powerful tool for addressing these limitations, offering the potential to predict CBR with greater accuracy and efficiency. This review paper aims to provide a comprehensive overview of the application of machine learning techniques for CBR prediction. The methodology involves a systematic review of existing literature, focusing on studies that employ ML models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forest (RF). Key findings from the reviewed studies are summarized, highlighting these techniques, the performance metrics, and the dataset size. The paper also discusses the advantages and limitations of ML in CBR prediction, including challenges related to data quality, model interpretability, and generalizability.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3153 - 3165"},"PeriodicalIF":0.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fire and smoke detection using adoption of machine learning algorithm for improving fire safety and disaster preparedness 采用机器学习算法进行火灾和烟雾探测，以提高消防安全和备灾能力

Asian Journal of Civil Engineering Pub Date : 2025-05-26 DOI: 10.1007/s42107-025-01360-5

S. Selvakumara Samy, Y. Sai Swarup, T. Sujith Kumar, C. Lakshmi Mani Shankar, S. Krishna Pradeep Reddy, J. S. Sudarsan, S. Nithiyanantham

{"title":"Fire and smoke detection using adoption of machine learning algorithm for improving fire safety and disaster preparedness","authors":"S. Selvakumara Samy, Y. Sai Swarup, T. Sujith Kumar, C. Lakshmi Mani Shankar, S. Krishna Pradeep Reddy, J. S. Sudarsan, S. Nithiyanantham","doi":"10.1007/s42107-025-01360-5","DOIUrl":"10.1007/s42107-025-01360-5","url":null,"abstract":"<div><p>Difficulties in effectively identifying and categorizing fires, particularly minor ones, within extensive forested areas globally. Due to detecting difficulties and hardware deployment challenges in remote sites, traditional approaches have difficulty implementing early warning systems in such circumstances. The study suggests machine learning algorithm based on Computer Vision model<b> (</b>YOLOv5), a cutting-edge object identification system, in conjunction with attention mechanisms as a solution to this problem. With this all-encompassing strategy, we hope to improve the recognition of small fire targets that are essential for early warning systems in forest areas. Computer Vision model<b> (</b>YOLOv5) achieved remarkable accuracy measures, such as a precision of 98.6%, recall of 90.2%, and an exceptional F1-score of 96%, indicating that the integration produced promising outcomes. The findings indicate noteworthy progress in the precision of detection, which is crucial for efficient handling of forest fires and prompt action to reduce any harm to property and casualties and loss of life. This kind of study will leads to improve fire safety and it will indirectly helps in effective disaster preparedness.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 7","pages":"3115 - 3129"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical analysis on shear behaviour of cold formed steel concrete composite beam with inverted U-shaped internal shear connector 倒u型内剪接头冷弯型钢-混凝土组合梁抗剪性能数值分析

Asian Journal of Civil Engineering Pub Date : 2025-05-26 DOI: 10.1007/s42107-025-01375-y

Badrinarayan Rath, T. R. Praveen Kumar, Eleni Bikila, Binaya Patnaik, Keerat Kumar Gupta

{"title":"Numerical analysis on shear behaviour of cold formed steel concrete composite beam with inverted U-shaped internal shear connector","authors":"Badrinarayan Rath, T. R. Praveen Kumar, Eleni Bikila, Binaya Patnaik, Keerat Kumar Gupta","doi":"10.1007/s42107-025-01375-y","DOIUrl":"10.1007/s42107-025-01375-y","url":null,"abstract":"<div><p>The utilization of cold-formed steel (CFS) in residential, low-rise commercial, and light industrial constructions has gained popularity owing to its lightweight and installation ease. This research investigates the shear behaviour of cold-formed U-shaped steel–concrete composite (CFSCC) beams incorporating internal shear connectors, comparing their performance to traditional reinforced concrete (RC) beams. Finite element models developed in ABAQUS were validated against experimental data for both CFSCC and RC beams, demonstrating satisfactory agreement. Subsequently, 30 finite element simulations were conducted to evaluate the impact of critical parameters such as width-to-height ratio (B/D), reinforcement ratio (RR), CFS thickness (Tcfs), and length-to-area ratio (Lsc/Asc) of shear connectors on structural performance. Results indicate shear capacity significantly correlates with the reinforcement ratio and CFS thickness. Specifically, shear capacity increased by 2.93% when the B/D ratio decreased from 0.75 to 0.6 and by an additional 8.16% when B/D reduced from 0.6 to 0.5. Increasing the shear reinforcement ratio from 0.4 to 0.5 enhanced shear capacity by 5.1%, while increasing CFS thickness from 1.5 mm to 2 mm improved shear capacity by 8.53%. Slip values for shear connectors varied significantly, with the lowest slip (6.2 mm) recorded for specimen RCS11 and the highest (16 mm) for RCS13. Furthermore, increasing CFS thickness from 1.5 mm to 2 mm reduced shear connector slip by 10.5%. Adequate shear connector distribution enabled the CFS sheet to effectively function as tension reinforcement, enhancing flexural performance, while reduced B/D ratios increased shear connector slip, and higher shear reinforcement ratios improved post-cracking beam behaviour.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3317 - 3340"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing failure mechanisms in reinforced concrete frame structures under thermo-mechanical loading using finite element analysis 钢筋混凝土框架结构在热机械载荷作用下的破坏机制分析

Asian Journal of Civil Engineering Pub Date : 2025-05-26 DOI: 10.1007/s42107-025-01374-z

N. Parthasarathi, M. Prakash, Denise-Penelope N. Kontoni

{"title":"Assessing failure mechanisms in reinforced concrete frame structures under thermo-mechanical loading using finite element analysis","authors":"N. Parthasarathi, M. Prakash, Denise-Penelope N. Kontoni","doi":"10.1007/s42107-025-01374-z","DOIUrl":"10.1007/s42107-025-01374-z","url":null,"abstract":"<div><p>Numerous studies have explored the failure mechanisms of reinforced concrete structures exposed to elevated temperatures. To simulate the action of fire on full-scale reinforced concrete buildings, four factors must be considered: the presence of loading, fire location, intensity, and duration. This is because the material behavior depends on the stress level, intensity, and duration of fire, and the sensitivity of the structural element to the location and application of fire. In this study, finite element analysis (FEA) was used to consider the combined effect of the mechanical loading and high temperature. To simulate the intensity and duration of the temperature rise, transient-state analysis must be performed. Two-dimensional, four-bay, three-story frames were analyzed under different cases of infill configurations subjected to high-temperature and working load conditions. The findings of this study related to the critical column of the frame, pattern of infill stresses, Demand Capacity Ratio (DCR), temperature, and time to failure were obtained and compared. The major conclusions are that the middle column is critical for both the bare frame and the infilled frame (with brick masonry and cement mortar interface) under high temperature and working load conditions. The investigation of the Bare Frame showed that the maximum vertical displacement is greater than that in the infilled frame, while the DCR is greater in the fully infilled frame, under high temperature at the first-story level (directly above the ground level) combined with working load conditions. Additionally, artificial neural network (ANN) models were developed to predict the vertical and lateral displacements observed in FEA during the transient-state analysis. Despite challenges in training ANNs, the models demonstrated strong potential in capturing complex structural behaviors under transient-state conditions.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3289 - 3315"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42107-025-01374-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving seismic performance of base isolated structures with a hybrid U-shaped steel damper as an isolator 混合u型钢阻尼器作为隔震器改善基础隔震结构的抗震性能

Asian Journal of Civil Engineering Pub Date : 2025-05-26 DOI: 10.1007/s42107-025-01372-1

Maheshwari S. Pise, D. V. Wadkar, Atulkumar A. Manchalwar

{"title":"Improving seismic performance of base isolated structures with a hybrid U-shaped steel damper as an isolator","authors":"Maheshwari S. Pise, D. V. Wadkar, Atulkumar A. Manchalwar","doi":"10.1007/s42107-025-01372-1","DOIUrl":"10.1007/s42107-025-01372-1","url":null,"abstract":"<div><p>Current earthquake-resistant design standards emphasize structural resilience by accounting for inelastic behaviour during major seismic events, particularly in steel and reinforced concrete (RC) buildings. This approach typically achieves controlled ductile performance, albeit with some structural damage. To minimize such damage, passive control systems are widely adopted. This study explores an advanced seismic mitigation strategy for RC frame buildings by incorporating a hybrid damping system at the base, which combines a U-shaped damper (USD) with a rubber core functioning as an isolator. The U-shaped elements, constructed from steel and aluminium, are modelled with elastoplastic material behaviour. At the same time, the rubber core is defined using the hyper-elastic Ogden model, ensuring an accurate representation of its nonlinear properties. Strategically positioned at the building's foundation, the USD synergises with the rubber core to enhance damping efficiency and energy dissipation during seismic events. Nonlinear Time History Analysis under four distinct ground motion scenarios was employed to evaluate the structure's seismic performance equipped with the USD-based isolator. The findings reveal a significant improvement in the structure's capacity to endure seismic forces compared to a counterpart without the USD system, demonstrating its superior effectiveness in mitigating earthquake-induced damage.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3279 - 3287"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145170289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of RC chimney design under multivariate loads: some insights by abaqus simulations 基于abaqus仿真的多变量荷载下钢筋混凝土烟囱设计优化研究

Asian Journal of Civil Engineering Pub Date : 2025-05-25 DOI: 10.1007/s42107-025-01368-x

Amit Gupta, Jonty Choudhary, Monika Sharma

{"title":"Optimization of RC chimney design under multivariate loads: some insights by abaqus simulations","authors":"Amit Gupta, Jonty Choudhary, Monika Sharma","doi":"10.1007/s42107-025-01368-x","DOIUrl":"10.1007/s42107-025-01368-x","url":null,"abstract":"<div><p>This research is an FEA of the RC chimney at the NMDC Steel Plant, Bastar, done through Abaqus. The structural evaluation takes wind load (44 m/s for the current plant) and reduction in temperature load up to 28<span>(^{circ })</span>C as per the guidelines of All India Basic Wind Speed into account. A detailed mesh convergence analysis was conducted, establishing an ideal mesh size of 1 mm, and a time step of 0.002 s was used for precise and effective simulation. The numerical values show the maximum displacement to be 27.56 mm and the maximum stress to be 7.414 <span>(times)</span> 10<sup>5</sup> MPa and the temperature is also within the ambient temperature which is 28 degree. All the result are within allowable limits for structural integrity. The analysis and checks has done by in accordance to IS 4998-2015. The analysis proves that the RC chimney is structurally sound under all the loading conditions applied. The present study brings out the necessity of precise FEA modeling and appropriate load combination considerations in providing long-term structural integrity to industrial chimneys. The results show the successful application of numerical modeling in simulating RC chimney behavior under wind and temperature actions, providing useful experience for future design, maintenance, and safety inspections of similar structures.</p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3131 - 3152"},"PeriodicalIF":0.0,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145168908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning methods for predicting the durability behavior of earth mortars with date palm ash 枣棕灰土砂浆耐久性预测的机器学习方法

Asian Journal of Civil Engineering Pub Date : 2025-05-23 DOI: 10.1007/s42107-025-01365-0

Khaled Athmani, Kamal Saleh Almeasar, Elhoussine Atiki, Adel Hassan Yahya Habal, Bachir Taallah, Abdelhamid Guettala

{"title":"Machine learning methods for predicting the durability behavior of earth mortars with date palm ash","authors":"Khaled Athmani, Kamal Saleh Almeasar, Elhoussine Atiki, Adel Hassan Yahya Habal, Bachir Taallah, Abdelhamid Guettala","doi":"10.1007/s42107-025-01365-0","DOIUrl":"10.1007/s42107-025-01365-0","url":null,"abstract":"<div><p>This study examines the use of machine learning models to predict the durability characteristics of earth mortars enhanced with date palm ash (DPA), a crucial factor in ensuring the long-term performance and sustainability of earthen construction. A comprehensive dataset derived from experimental investigations was used to train and validate two models: An Artificial Neural Network hybridised by Neural Architecture Search (NAS-ANN) and a Random Forest with Neural Architecture Search (NAS-RF). Five key durability parameters, initial durability, capillary absorption, abrasion resistance, mass loss due to abrasion, and swelling behavior, were selected as outputs based on their relevance to structural integrity and longevity. The K-fold cross-validation technique rigorously assessed each model's predictive capabilities. Results indicate that the NAS-ANN model consistently outperforms the other models across all durability parameters, demonstrating superior accuracy and robustness. Across all parameters, the NAS-ANN model exhibits superior predictive performance compared to the NAS-RF model, accurately capturing complex relationships between material composition and long-term performance. These findings highlight the efficacy of DPA as a sustainable additive for enhancing the mechanical and physical properties of earth mortars, offering a promising avenue for environmentally responsible construction practices. The NAS-ANN model's accurate predictive capabilities provide a valuable tool for optimizing material design, creating durable and sustainable earth-based structures that withstand diverse environmental conditions. This research supports the broader adoption of DPA-modified earth mortars as a viable alternative to conventional building materials, promoting resource efficiency and reducing environmental impact within the construction industry. </p></div>","PeriodicalId":8513,"journal":{"name":"Asian Journal of Civil Engineering","volume":"26 8","pages":"3211 - 3231"},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145168373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0