Results in Engineering最新文献

{"title":"Automatic visual lip reading: A comparative review of machine-learning approaches","authors":"Khosro Rezaee ,&nbsp;Maryam Yeganeh","doi":"10.1016/j.rineng.2025.107171","DOIUrl":"10.1016/j.rineng.2025.107171","url":null,"abstract":"<div><div>Automatic lip-reading systems are evolving from traditional handcrafted pipelines to advanced deep and hybrid architectures that integrate local motion modeling with long-range temporal context. This review provides a comprehensive synthesis of classical techniques and state-of-the-art learning approaches, with a specific focus on hybrid three-dimensional convolution plus Transformer or Conformer backbones and on multimodal training strategies that enable visual-only inference. Unlike previous surveys, we critically appraise datasets through the lenses of diversity, realism, robustness, and efficiency, and we foreground responsible deployment by addressing privacy, fairness, and transparency. We propose a clear taxonomy that spans classical, hybrid, and Transformer-based models. We compare their strengths and limitations for both word- and sentence-level recognition, and analyze the trade-offs between accuracy, computational cost, latency, and interpretability. The evidence indicates that lightweight hybrid models offer high accuracy with practical efficiency and that audio-as-teacher training significantly improves visual reliability when audio is unavailable. However, progress remains constrained by limited demographic and linguistic coverage, a reliance on studio-style capture, and uneven robustness to real-world challenges like pose, illumination, motion blur, and occlusion. The review concludes with a focused call to action: we must build multilingual and demographically balanced corpora with standardized robustness testing; develop parameter-efficient hybrid backbones suitable for edge deployment; adopt self-supervised and semi-supervised learning to reduce annotation demands; and report calibrated uncertainty, fairness diagnostics, and transparent documentation. These recommendations are intended to guide researchers toward creating scalable, reliable, and trustworthy lip-reading systems for real-world applications.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107171"},"PeriodicalIF":7.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047283","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}

{"title":"Modification strategies of conductive polymers with advanced carbon materials for energy and environmental solutions","authors":"Mohsen Ahmadipour ,&nbsp;Muhammad Saqlain Iqbal ,&nbsp;Muhammad Athar Saeed ,&nbsp;Azrul Azlan Hamzah ,&nbsp;Aaiza Ramzan ,&nbsp;Anish Bhattacharya ,&nbsp;Ujjwal Pal ,&nbsp;Masoud Ahmadipour ,&nbsp;Ai Ling Pang ,&nbsp;Meenaloshini Satgunam","doi":"10.1016/j.rineng.2025.107168","DOIUrl":"10.1016/j.rineng.2025.107168","url":null,"abstract":"<div><div>Environmental remediation has become an urgent necessity, with water security emerging as a primary global concern. To address this challenge, the development of affordable and sustainable materials is essential, particularly for improving accessibility in remote regions. Among emerging candidates, Conductive Polymers (CPs) have gained significant attention due to their sustainable synthesis using mild chemicals and their ability to bypass energy-intensive processing routes. The delocalization of π-electrons along their conjugated backbones enables efficient charge transport, allowing them to function as photocatalysts while simultaneously adsorbing pollutants. This dual property not only supports environmental remediation but also extends their application to energy generation and storage technologies. Another promising class of materials, Carbon Nanostructures (CNS), offers excellent charge transfer rates and structural tunability. However, their high production cost often limits large-scale applications. To overcome these limitations, recent studies have explored the synergy between CPs and CNS, leading to the design of advanced composites through methods such as in situ polymerization, electrodeposition, and aerogelization. These hybrid materials have demonstrated superior photocatalytic performance, making them attractive for fabricating electrodes used in various remediation strategies. Such electrodes have been successfully applied in hydrogen and oxygen evolution reactions, carbon dioxide capture, dye degradation, and the removal of heavy metals and pharmaceuticals. Beyond environmental cleanup, processes like hydrogen and oxygen evolution also provide alternative energy pathways, thereby linking remediation with sustainable energy production. This review highlights recent developments, along with other innovative materials and waste valorization strategies, underscoring their potential in fostering a greener and more resilient ecology.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107168"},"PeriodicalIF":7.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047285","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}

{"title":"Performance analysis of red mud concrete pier columns in coal pillarless mining and roadway deformation prediction based on machine learning","authors":"Yanhui Zhu ,&nbsp;Ye Tian ,&nbsp;Peilin Gong ,&nbsp;Kang Yi ,&nbsp;Guang Wen","doi":"10.1016/j.rineng.2025.107166","DOIUrl":"10.1016/j.rineng.2025.107166","url":null,"abstract":"<div><div>To reduce concrete costs in pillarless coal mining and mitigate environmental impacts of red mud, this study integrates onsite research, numerical simulation, theoretical analysis, laboratory testing, and machine learning to develop a genetic algorithm-optimized AdaBoost prediction model for roadway deformation control using 20 % red mud concrete pier columns. Laboratory results demonstrate that the 20 % red mud concrete achieves balanced strength development, providing sufficient early strength (e.g., 16 MPa at 7 days) and high mid-to-late stage strength (e.g., 26.9 MPa at 28 days). Field implementation at Xiegou Mine’s 23,111 working face, validated by onsite monitoring, confirms that these columns effectively stabilize roadway deformation, limiting top and bottom slab displacements to 480 mm and 260 mm respectively at 1000 m mining distance—well within design tolerance. The prediction model exhibits high accuracy (MSE: 0.7830, RMSE: 0.8465, MAE: 0.4721, MAPE: 0.0342), with field data closely matching predicted deformation trends and ultimate limits. This high accuracy ensures the safe mining of the 23,111 working face.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107166"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047234","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}

{"title":"A mixed-method comparative analysis of sustainable roofing solutions for thermal and energy efficiency in residential buildings in Saudi Arabia","authors":"Raheemat O. Yussuf ,&nbsp;Omar S. Asfour ,&nbsp;Ahmed Abd El Fattah ,&nbsp;Muhammad Asif","doi":"10.1016/j.rineng.2025.107159","DOIUrl":"10.1016/j.rineng.2025.107159","url":null,"abstract":"<div><div>There is a growing need for practical solutions that are climate responsive, particularly in hot arid regions like Saudi Arabia. This study explores the potential of four sustainable roofing strategies, namely: green roof (GR), cool roof (CR), solar PV roof (SPV), and roof canopy (RC), to reduce rooftop surface temperatures and improve energy performance of residential buildings considering three cities that represent three climatic zones in Saudi Arabia. The study used a combination of qualitative and quantitative methods based on a survey of residents, and thermal performance simulations of a case study. The survey results showed that all of the investigated roofing strategies were positively perceived by residents, with weighted average agreement levels ranging between 3.8 and 4.4 out of 5.0. The thermal simulation results showed that the investigated roofing strategies offered a reduction in roof external surface temperature, which was more significant in GR, where a reduction of 28% to 52% was observed compared to the reference flat roof (FR). As for energy consumption, GR showed a higher potential, where a reduction of 20% was observed. The findings highlight the importance of informed decision-making and innovative sustainable design strategies in overcoming thermal design challenges posed by extreme hot climatic conditions.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107159"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047515","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}

{"title":"Research and optimization of configurable modular thermal management system for multi-ambient temperatures","authors":"Xiaoyong Gu ,&nbsp;Guojie Chao ,&nbsp;Ye Zou ,&nbsp;Xiang Jiao ,&nbsp;Biwen Chen","doi":"10.1016/j.rineng.2025.107164","DOIUrl":"10.1016/j.rineng.2025.107164","url":null,"abstract":"<div><div>It is crucial to keep the temperature of lithium-ion batteries within a reasonable range. This study presents a configurable modular thermal management system that integrates freely configurable active and passive thermal management modules to meet diverse application demands. A bio-based phase change material (PCM) with a phase transition temperature of 40.1°C was developed for a passive thermal management module. A model of battery thermal management was developed to assess the impacts of PCM geometry and active thermal management parameters on battery pack temperatures. Building on this, the real-world applicability of the thermal management system was evaluated across diverse cities, leading to optimized solutions tailored to each city. The results indicate that increasing the PCM height enhances cooling capacity by 26%, but extends heating time by 75% compared to increasing its width. Raising the heating temperature from 35°C to 45°C shortens heating time by 45%, but increases energy consumption by 49%. High-temperature cities require more active thermal management modules, maintaining battery pack temperature less than 45°C at a 42°C ambient temperature. Temperate cities maximize passive module integration, achieving a battery pack temperature of less than 45°C at a 38°C ambient temperature without energy consumption. Low-temperature cities utilize heating plate substitution for an active thermal management module, yielding 10% energy savings. This research provides a reference basis for the direct selection and application of the configurable modular thermal management system in diverse scenarios.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107164"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027625","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}

{"title":"Dual-mode optimal predictive control of a wind driven multi-phase PMSG: A hybrid approach to grid and standalone applications","authors":"Mahmoud A. Mossa ,&nbsp;Hussein Mahmoud ,&nbsp;Ahmed A. Hassan ,&nbsp;Ameena Saad AL-Sumaiti","doi":"10.1016/j.rineng.2025.107105","DOIUrl":"10.1016/j.rineng.2025.107105","url":null,"abstract":"<div><div>Renewable energy sources (RES) have been receiving much interest as an achievable solution to the world's environmental problems. The aim of the present paper is to design a predictive control strategy that enhances the quality of generated power from a wind turbine system. The study begins by thoroughly describing the system model, encompassing the wind turbine, the five-phase PMSG, and the integrated battery system. Subsequently, optimization technique such as MPPT is applied to maximize the wind power. A comprehensive investigation is conducted on the performance of a wind energy conversion system (WECS) under two modes of operation: grid connection, and standalone which is integrated with a battery bank and a bi-directional converter. The proposed predictive voltage control (PVC) algorithm demonstrated superior dynamic response and significantly reduced ripple fluctuations compared to the well-known predictive torque control (PTC) and predictive current control (PCC). The analysis further revealed that the PVC algorithm successfully minimized voltage oscillations and current harmonics without relying on machine parameter variations, which contributes to a more stable and efficient operation. Through simulations, the controller's capacity to regulate electrical power between the generator, load, and battery was demonstrated, showing balanced and seamless charging and discharging operations. Overall, the findings confirm that the proposed PVC approach enhances the operational efficiency of WECS by improving power quality, minimizing system dependability, and ensuring robust power flow management. These outcomes provide a strong foundation for implementing this control strategy in practical applications, advancing the performance and dependability of renewable energy systems. In summary, the proposed PVC demonstrated superior performance in comparison with other control techniques; this has been translated in the form of THD reduction with percentages of 60 % compared to PTC and 28 % compared to PCC. Additionally, the computation burden with the proposed PVC recorded a reduction with percentages of 28.3 % compared to PTC and 23 % compared to PCC.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107105"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047546","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}

{"title":"Waste‑to‑hydrogen technologies: Advances in catalytic, thermochemical, and biochemical conversion pathways for a circular hydrogen economy","authors":"Ganesan Subbiah ,&nbsp;Ritesh Pratap Singh ,&nbsp;Chilukuri Sulakshana ,&nbsp;Sikata Samantaray ,&nbsp;Shivendu Saxena ,&nbsp;Somashekar DP ,&nbsp;Prem Nath Suman ,&nbsp;Kamakshi Priya K","doi":"10.1016/j.rineng.2025.107157","DOIUrl":"10.1016/j.rineng.2025.107157","url":null,"abstract":"<div><div>The evolution towards a circular hydrogen economy requires the deployment of sophisticated technologies capable of transforming various waste streams into high-purity hydrogen while minimizing environmental impacts. This review presents a comprehensive evaluation of recent advancements in catalytic, thermochemical, and biochemical methodologies, highlighting their operational efficacy, techno-economic viability, and environmental sustainability. Catalytic methodologies, including nanostructured, photocatalytic, and electrocatalytic systems, have achieved hydrogen production rates of 100–250 mL H₂ g⁻¹ h⁻¹ with Faradaic efficiencies of 80–90 %. However, obstacles such as catalyst deactivation and scalability issues persist. Thermochemical methodologies, encompassing pyrolysis, gasification, and plasma-assisted reforming, generate syngas comprising 20–55 vol% H₂ with energy demands of 0.6–0.8 mol H₂ kWh⁻¹; however, they necessitate trade-offs between capital intensity and operational expenses. Biochemical techniques, such as dark fermentation (DF), photofermentation (PF), and microbial electrolysis cells (MECs), exhibit yields of 2–6 mol H₂ mol⁻¹ substrate under moderate conditions, with potential for co-product valorization, yet constrained by sluggish kinetics and pretreatment requirements. Comparative life-cycle assessment (LCA) and techno-economic analysis (TEA) suggest that hybrid systems amalgamating thermochemical and biochemical pathways can achieve costs as low as 1.8–2.5 USD kg⁻¹ H₂ and lifecycle emissions below 2 kg CO₂ kg⁻¹ H₂, thereby surpassing single-process configurations.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107157"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047288","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}

{"title":"Gradient structural disorder induces isotropic and high-energy-absorbing behavior in porous Ti-6Al-4V Alloy","authors":"Shiyue Guo ,&nbsp;Rusheng Zhao ,&nbsp;Huiling Tang ,&nbsp;Xiangyu Guo ,&nbsp;Jian Wang ,&nbsp;Haitao Yang ,&nbsp;Fan Zhang","doi":"10.1016/j.rineng.2025.107163","DOIUrl":"10.1016/j.rineng.2025.107163","url":null,"abstract":"<div><div>Porous Ti-6Al-4V alloys, renowned for their lightweight nature and exceptional energy-absorption capabilities, hold great promise for aerospace and biomedical applications. However, their widespread adoption has been limited by challenges such as mechanical anisotropy and localized stress concentrations. In this study, we propose novel gradient-disordered porous architectures fabricated via advanced laser powder bed fusion (L-PBF) to overcome these issues. Trapezo-rhombic dodecahedron cells were employed as the basic structural unit, and gradient-disordered layers (1–4) were strategically integrated to improve mechanical performance through controlled heterogeneity. Experimental results revealed that the gradient-disordered designs significantly enhanced energy absorption, achieving increases of up to 600% along the <em>y</em>-axis and 300% along the <em>x</em>-axis compared with ordered structures. Furthermore, these architectures reduced anisotropy in normalized Young’s modulus and energy absorption by 96% and 93%, respectively, resulting in nearly isotropic behavior. Compression tests and finite element simulations confirmed improved isotropy, suppression of shear band development, and more uniform stress distribution, underscoring the robustness of the proposed designs. Overall, these findings highlight gradient-disordered porous architectures as a promising strategy for optimizing porous Ti-6Al-4V alloys, particularly in aerospace and biomedical applications requiring high energy absorption, isotropy, and durability.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107163"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020855","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}

{"title":"AI-assisted multi-objective optimization and performance analysis of a solar-driven hybrid system for power generation, desalination and fuel synthesis","authors":"Seyed Farhan Moosavian,&nbsp;Ahmad Hajinezhad","doi":"10.1016/j.rineng.2025.107161","DOIUrl":"10.1016/j.rineng.2025.107161","url":null,"abstract":"<div><div>This study evaluates the performance of a multipurpose, self-sufficient system comprising a heliostat solar farm, a central thermal receiver, supercritical CO₂ Brayton cycles, an organic Rankine cycle (ORC), a reverse osmosis (RO) unit, a PEM electrolyzer, a CO₂ absorption unit, and a methanol synthesis unit. The aim was to achieve sustainable production through the integration of bioproducts while maximizing the technical and economic potential of the design. The system was assessed to be attractive for investment in terms of both performance and cost-effectiveness. Simulation results indicate that the proposed configuration can generate 4.69 MW of power from the supercritical CO₂ Brayton cycle and 383 kW from the ORC, while producing 0.2 m³/h of freshwater, 88 kg/h of CO₂, 14 kg/h of hydrogen, and 63 kg/h of methanol, with an overall exergy efficiency of 52.6 %. In the final stage, an artificial neural network (ANN) was developed using machine learning techniques, and the system was optimized via the Gray Wolf algorithm considering five decision variables across two-, three-, four-, five-, and six-objective modes. The six-objective scenario achieved the best performance, yielding an exergy efficiency of 54.18 %, a total cost rate of 6376 $/h, hydrogen and methanol production rates of 16.87 kg/h and 65.3 kg/h, respectively, and LCOE and LEIOE values of 0.0744 $/kWh and 20.45 Pts/MWh.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107161"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047290","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}

{"title":"Low-dimensional representation and prediction of supersonic gas-solid two-phase flow field based on CAE-BiLSTM","authors":"Liangliang Zhang,&nbsp;Zhixun Xia,&nbsp;Likun Ma,&nbsp;Yunchao Feng,&nbsp;Binbin Chen,&nbsp;Pengnian Yang,&nbsp;Luxi Xu","doi":"10.1016/j.rineng.2025.107165","DOIUrl":"10.1016/j.rineng.2025.107165","url":null,"abstract":"<div><div>Dynamic monitoring and rapid prediction of supersonic gas-solid two-phase flow fields are critical for the optimal design and flow control of solid rocket scramjets. This study proposes a hybrid reduced-order model (ROM) based on convolutional autoencoder (CAE) and bidirectional long short-term memory (BiLSTM) network (CAE-BiLSTM) to achieve efficient prediction of solid particle clusters’ distribution in such flow fields. High-dimensional flow field data (102,400 dimensions) were compressed into a low-dimensional latent space (128 dimensions, compression ratio 0.125 %) using CAE, which outperformed the traditional proper orthogonal decomposition (POD) in low-dimensional representation and exhibited a 3 % higher mean structural similarity index (SSIM) in flow field reconstruction. POD analysis revealed that the flow field is dominated by low-order modes, with the first mode contributing 21.1 % of the total energy, while the cumulative energy of the first 50 modes accounted for 61 %. The CAE-BiLSTM model effectively predicted the macroscopic distribution of solid particle clusters within the engine combustor flow field during short-term evolution, achieving a mean SSIM of 0.8814 for single-step prediction and 0.8545 for five-step recursive prediction, capturing the high-dimensional spatiotemporal dynamics of the flow field. However, long-term prediction accuracy deteriorated due to error accumulation. This study provides a novel approach for rapid flow field prediction, demonstrating potential applications in engine design and flow control.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107165"},"PeriodicalIF":7.9,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047545","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}