Engineering reports : open access最新文献

{"title":"Structured Extraction of Atomic Rules From Chinese Water-Governance Regulatory Texts With Inheritance Reconstruction","authors":"Yuanbin Wang,&nbsp;Xiaoyao Xie,&nbsp;Heng Wang,&nbsp;Shuai Jiang,&nbsp;Qiuhua Li,&nbsp;Mengshu Han,&nbsp;Chuqi Ruan,&nbsp;Liuyuan Chen","doi":"10.1002/eng2.71086","DOIUrl":"https://doi.org/10.1002/eng2.71086","url":null,"abstract":"<p>Chinese water-governance regulatory texts often contain multi-level enumerations, implicit arguments, shared conditions, proviso clauses, and legal consequences spanning multiple clauses. These structures make end-to-end rule extraction prone to unstable boundaries and inconsistent slot attribution. This paper proposes SARE-IR, a structure-aware method that represents each atomic rule as a 10-tuple comprising type, deontic, subject, action, object, conditions, exceptions, scope, purpose, and refers_to. The pipeline combines conservative structural segmentation, schema-constrained fragment extraction, context-sensitive inheritance, and deterministic structural and normative-semantic normalization. We evaluate all 10 slots on 247 provisions containing 658 gold rules. Under the revised protocol, SARE-IR obtains 0.4796 relaxed skeleton F1, 0.7754 null-inclusive 10-slot F1, and 0.3367 complete 10-slot exact F1. A matched Fragment-Direct control uses the same Qwen2.5-14B backbone, fragments, decoding limits, retry policy, seed, and hardware but omits structural context and method-specific normalization; the logged Full pipeline improves relaxed skeleton F1 by 0.2894 (95% CI [0.2371, 0.3412]) and complete-rule exact F1 by 0.2873 (95% CI [0.2362, 0.3378]). Stage-wise analysis shows that final semantic normalization is a substantive component of the method, while individual structural heuristics have selective rather than uniformly positive effects. SARE-IR provides an auditable framework for regulatory knowledge-graph construction and structured legal knowledge services.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145893","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}

{"title":"Quantifying Shuttlecock Skill Progression via Multimodal Action Recognition and Dynamics-Guided Trajectory Prediction","authors":"Chao Zhang,&nbsp;Fei Zeng","doi":"10.1002/eng2.71080","DOIUrl":"https://doi.org/10.1002/eng2.71080","url":null,"abstract":"<p>The fundamental techniques of shuttlecock kicking are characterized by high speed, complex structure, and sensitivity to details, making it difficult for beginners to establish stable movement patterns within a short timeframe. This study proposes a multimodal feature fusion-based action recognition and trajectory prediction framework to quantitatively evaluate the effectiveness of compensatory exercises in accelerating shuttlecock skill acquisition. The system comprehensively employs TrackNet, Faster R-CNN, and HRNet to extract shuttlecock trajectories, player positions, and human pose information. It constructs two pose representation methods that keypoint coordinate and heatmap encoding, and unifies multi-modal features through a multi-core fusion strategy. Subsequently, sequence models including LSTM, GRU, and Transformer are employed to predict future hitting trajectories. Stability and consistency analyses are conducted through velocity decay fitting, landing point deviation distribution, and action confusion matrices. Experimental results show that compensatory training produced stable exponential decay constants ranging from <i>τ</i> = 0.71 to 0.84 s, indicating smoother energy dissipation and improved movement stability, while landing point deviations became more concentrated and action recognition accuracy increased significantly. These findings demonstrate that the proposed framework effectively enhances the regularity, predictability, and quantitative assessment of shuttlecock skill acquisition.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145605","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}

{"title":"Artificial Intelligence in Invisible Orthodontics: From Digital Impressions to Adaptive Treatment Management","authors":"Soodeh Hosseini,&nbsp;Hossein Seilani,&nbsp;At-har Nasari","doi":"10.1002/eng2.71099","DOIUrl":"https://doi.org/10.1002/eng2.71099","url":null,"abstract":"<p>Digital transformation in orthodontics has significantly revolutionized clinical practices over recent decades. Advancements such as intraoral scanners, 3D imaging (including cone-beam computed tomography, CBCT), and advanced treatment planning software have increased diagnostic accuracy and the ability to design personalized treatments. These technologies have primarily focused on static aspects and still require continuous human oversight. Machine learning algorithms, particularly convolutional neural networks (CNNs) and artificial neural networks (ANNs), offer superior performance in tasks such as identifying anatomical landmarks on radiographic images, assessing skeletal maturity, and predicting treatment outcomes. Research has shown that AI in static diagnosis and planning has achieved an accuracy greater than 90%, outperforming traditional methods. Moreover, AI reduces processing time, minimizes operator performance variability, and serves as a supportive tool in digital orthodontic workflows. Despite these advancements, there remains a significant gap in research regarding adaptive AI for treatments involving clear aligners. Most studies focus on static planning, while dynamic aspects, such as real-time treatment adjustments based on the patient's biological responses or deviations in tooth movement, are less explored. This research gap may arise from factors such as patient biological diversity, a lack of real clinical data, and the need for multi-center validation. Adaptive AI, based on reinforcement learning and digital twin modeling, has the potential to reduce the average treatment duration by approximately 3 to 4 months and increase patient satisfaction. The aim of this review is to provide a comprehensive examination of AI's role in real-time management of invisible orthodontic treatments, focusing on clear aligner-based treatments. This study analyzes AI applications going from digital data processing to integration with supervisory platforms, discussing challenges, limitations, and future perspectives. This review not only summarizes current achievements but also proposes practical solutions to overcome existing barriers and presents adaptive AI as a pivotal tool for the future of orthodontics.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145607","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}

{"title":"A Critical Analysis of Optimization Algorithms for Cultural Heritage Conservation and Management","authors":"Eslam Mohammed Abdelkader,&nbsp;Abobakr Al-Sakkaf,&nbsp;Moaaz Elkabalawy,&nbsp;Kyrillos Ebrahim,&nbsp;Haytham Elmousalami,&nbsp;Mohammed Algamati,&nbsp;Ghasan Alfalah","doi":"10.1002/eng2.71060","DOIUrl":"https://doi.org/10.1002/eng2.71060","url":null,"abstract":"<p>Heritage buildings symbolize cultural identity, architectural character, and historical epitome of communities. World heritage sites are extensively used in marketing campaigns, and they act as an alluring means for promoting tourism development. Heritage conservation has emerged and evolved significantly in global society. In recent years, optimization algorithms have been applied across multiple decision-making domains related to heritage buildings. However, their applications are fragmented across different research areas and lack a comprehensive synthesis. In light of the foregoing, this research study synthesizes the existing literature across six key multidisciplinary domains associated with the planning, conservation, and management of cultural heritage, namely: heritage conservation and restoration, structural analysis and seismic retrofitting, tourism and visitor development, sustainability performance analysis, adaptive reuse, and emergency evacuation. With that said, the paper introduces a mixed-review method approach that blends systematic literature review with scientometric analysis to analyze relevant literature pertaining to the use of optimization algorithms (exact and metaheuristics) in the major functional and management domains of heritage buildings. This study establishes a reference for developing future driven optimization models for decision-making in the planning, conservation, and management of cultural heritage.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145770","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}

{"title":"A Comprehensive Review of GAN-CNN Hybrid Methods for Intelligent Fault Diagnosis of Rotating Machinery","authors":"Temesgen Tadesse Feisa,&nbsp;Fasikaw Kibrete,&nbsp;Yitbarek Gashaw Tadesse,&nbsp;Abdu Mohammed Seid,&nbsp;Sewale Yasabu Enyew,&nbsp;Getachew Getu Enyew,&nbsp;Mulugeta Linger Tariku,&nbsp;Zewdie Alemayehu Mulat","doi":"10.1002/eng2.71097","DOIUrl":"https://doi.org/10.1002/eng2.71097","url":null,"abstract":"<p>Rotating machinery plays a vital role in modern industry and daily life, with widespread applications across sectors such as aerospace, manufacturing, and transportation. However, prolonged operation under harsh and variable conditions increases the likelihood of mechanical failures, which can lead to system-wide disruptions, costly downtime, and serious safety risks. In recent years, artificial intelligence-based methods, particularly hybrid deep learning approaches, have gained significant attention for their ability to provide timely and accurate fault diagnosis in rotating machinery. Among these, the integration of generative adversarial networks (GANs) and convolutional neural networks (CNNs) has shown promising potential. Despite growing interest, to the best of the authors' knowledge, no comprehensive review has yet been conducted focusing specifically on hybrid fault diagnosis methods that combine GANs and CNNs. This paper aims to fill that gap by providing a thorough review of current research on hybrid GAN-CNN-based fault diagnosis methods for rotating machinery. The review systematically synthesizes 217 peer-reviewed publications, international standards, and authoritative technical resources identified using predefined inclusion and exclusion criteria. The literature search covered two major databases, Scopus and Web of Science, and spanned the period from 2010 to 2026. First, the fundamental principles and architectures of GANs and CNNs, along with their variants, are presented. Next, existing hybrid GAN-CNN methods tailored for fault diagnosis are systematically reviewed, including their improvements and applications in the field. The paper then discusses the advantages and limitations of various GAN and CNN methods. Based on the presented review, existing challenges and future research directions are examined, followed by a conclusion.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145771","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}

{"title":"A State-of-the-Art Comprehensive Review: Application of Artificial Intelligence in Predicting the Load-Bearing Capacity of Piles","authors":"Mohammadreza Ahmadi Golsefidi,&nbsp;Mahzad Esmaeili-Falak","doi":"10.1002/eng2.71085","DOIUrl":"https://doi.org/10.1002/eng2.71085","url":null,"abstract":"<p>Artificial intelligence models have widely replaced traditional statistical modeling tools as reliable alternatives for capacity estimation. Estimating the load-bearing capacity of piles using analytical formulas can yield a range of results, which can be attributed to the simplifying assumptions incorporated into the models. Another innovative method for predicting the load-bearing capacity of piles is the pile dynamic analysis test, which is based on the theory of one-dimensional wave propagation. Simpler methods such as field tests like the cone penetration test and standard penetration test have also been proposed by geotechnical engineers for evaluating pile capacity. This article provides an advanced review by organizing, summarizing, and categorizing the results of the most commonly used machine learning methods, innovative algorithms, and combined approaches-based data from static and dynamic loading tests and in situ tests in determining the load-bearing capacity of piles. To this end, 135 articles published in the past three decades were considered, taking into account reputable journals, top researchers, country contributions, and research institutions to highlight the annual research trends in this field. The paper presents a review of the application of various artificial intelligence algorithms such as ANN, GP, GB, regression algorithms, RF, SVM, DT, and Fuzzy logic in determining the load-bearing capacity of piles. Additionally, the sub-branches related to the ANN and GB algorithms were examined, and finally, studies conducted using optimization algorithms in conjunction with all the artificial intelligence methods were reviewed and presented. Furthermore, artificial intelligence techniques were classified into separate clusters using the VOSviewer clustering program, and their relationships were visualized through the thickness of connecting lines to identify their application domains. These findings can serve as a guide for researchers seeking to utilize artificial intelligence techniques in the field of pile load-bearing capacity in the future.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083945","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}

{"title":"TrustSpec: Simulation-Grounded Physics-Driven Spectral Inversion With Uncertainty Quantification for SiC Epitaxial Thickness Metrology","authors":"Zijie Nie,&nbsp;Shunlin Yang,&nbsp;Qingjie Guo","doi":"10.1002/eng2.71088","DOIUrl":"https://doi.org/10.1002/eng2.71088","url":null,"abstract":"<p>Accurate thickness metrology is essential for silicon carbide (SiC) epitaxial layers, yet classical Fourier-transform infrared (FTIR) fringe analysis relies on artifact-specific preprocessing, degrades below the fringe-resolution limit, and provides no calibrated confidence for individual measurements. This paper presents TrustSpec, a simulation-grounded, physics-driven spectral inversion framework intended as a proof of concept for trustworthy SiC epitaxial thickness metrology. A dispersive two-interface interference model with randomized instrument disturbances is used as a spectral digital twin to generate labeled training spectra, and the same twin is reused at inference time as an analysis-by-synthesis referee. A deep ensemble estimates thickness from a physics-conjugate Fourier-magnitude optical-thickness representation; the ensemble sample standard deviation and a windowed re-synthesis consistency ratio define a two-channel trust plane for release, review, or rejection. In a reproducible simulation study over 0.4–25 μm, TrustSpec achieves a mean absolute error (MAE) of 0.110 μm and remains effective below 1 μm, where a classical FFT pipeline fails. Split-conformal recalibration yields 94.6% empirical coverage for a nominal 95% interval. The combined trust policy releases 90.5% of in-distribution spectra at an MAE of 0.066 μm and rejects all 600 tested simulated 28–38 μm thickness-extrapolation spectra; a 25–28 μm test shows a gradual rejection transition near the training boundary. Channel ablations, referee-window sensitivity, shifted-nuisance stress tests, and model-mismatch experiments delimit the scope of these simulation results and motivate batch residual monitoring, reference-wafer checks, and periodic two-angle acquisition for drift detection. Validation on measured SiC wafers remains necessary before production deployment.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71088","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083944","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}

{"title":"Influence of Mechanochemical Pretreatment on the Activation Behavior of Bentonite With Respect to Oil Bleaching Performance","authors":"Rahman Ahmadi,&nbsp;Hossein Heydari,&nbsp;Behzad Shahbazi","doi":"10.1002/eng2.71076","DOIUrl":"https://doi.org/10.1002/eng2.71076","url":null,"abstract":"<p>This study systematically investigates the effect of mechanochemical pretreatment followed by controlled acid activation on the bleaching performance of bentonite in palm oil. Raw bentonite was mechanically milled for different durations to reduce particle size and induce lattice disorder, creating highly accessible sites for subsequent sulfuric acid activation. Structural and physical modifications, including increased structural disorder and particle size reduction, were evaluated using XRD, XRF, and particle size analysis. The optimally activated bentonite (120 min milling, 2 M H₂SO₄, 10 wt.% solid to acid ratio, 1 wt.% dosage, 90°C, 30 min) achieved a maximum bleaching efficiency of 98.5%. Adsorption isotherms showed that pigment removal follows the Freundlich model, indicating multilayer adsorption on a heterogeneous surface. This work demonstrates that combining mechanochemical and acid activation effectively enhances bentonite's structural and functional properties, providing a practical strategy for high-performance oil bleaching.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149084095","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}

{"title":"Nanotechnology-Driven Analysis of MHD Maxwell-Casson Nanofluid Flow With Activation Energy Using Artificial Neural Networks","authors":"D. Prabu,&nbsp;Shajar Abbas,&nbsp;Abdul Raqib Muslimyar,&nbsp;Razaullah Hafiz Ullah,&nbsp;Ruzimurod Abiyev,&nbsp;Emad A. Az-Zo'bi","doi":"10.1002/eng2.71064","DOIUrl":"https://doi.org/10.1002/eng2.71064","url":null,"abstract":"<p>The Maxwell-Casson nanofluid (NF) flow past a porous inclined plate has attracted much attention, since it has extensive potential applications in thermal energy systems, chemical processes, biomedical transport, and advanced cooling technology. This paper aims to simulate the flow and heat and mass transfer (HMT) characteristics of Maxwell-Casson NF past an inclined porous plate under the influence of a magnetic field, Darcy-Forchheimer porous resistance, thermal radiation, and a chemical reaction with activation energy. A Casson parameter is included in the mathematical modeling for the yield stress nature of the fluid, and Maxwell relaxation time to describe the viscoelasticity of the fluid. The momentum equation contains Darcy-Forchheimer drag, Lorentz forces, and thermal and solutal buoyancy factors; an energy equation involving viscous dissipation, thermal radiation, and internal heat generation is utilized; a temperature-dependent chemical reaction with Arrhenius activation energy is incorporated in the mass transfer equation. The problem is described by nonlinear boundary layer governing equations, which are solved numerically through the help of the MATLAB bvp4c method, and a feedforward artificial neural network (ANN) is developed to predict the velocity, temperature, and concentration profiles. Our results demonstrate that the magnetic field strength and porous resistance suppress the motion of fluid, while buoyancy effects tend to enhance velocity distribution. Thermal radiation, viscous dissipation, and activation energy have a significant effect on the thermal and concentration distributions. The predicted results using ANN are found to be in excellent agreement with numerical outcomes; this confirms the validity of the proposed data-driven strategy. From this, an understanding of the interaction of Casson yield-stress, Maxwell relaxation time, nanoparticles, magnetic field, porous resistance, and activation energy has been assessed for complex non-Newtonian NF flow.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083962","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}

{"title":"Correction to “Optimization of Material Density and Strength in Super Duplex 2507 Stainless Steel via Selective Laser Melting: CCD-PSO-DFA Approach”","authors":"","doi":"10.1002/eng2.71092","DOIUrl":"https://doi.org/10.1002/eng2.71092","url":null,"abstract":"<p>\u0000 <span>T. Ramesh</span>, <span>N. Hiremath</span>, <span>A. Lakshmikanthan</span>, et al., “ <span>Optimization of Material Density and Strength in Super Duplex 2507 Stainless Steel via Selective Laser Melting: CCD-PSO-DFA Approach</span>,” <i>Engineering Reports</i> <span>8</span>, no. <span>9</span> (<span>2026</span>): e71071, https://doi.org/10.1002/eng2.71071.</p><p>In the published version of the article, the name of the first author was incorrect. The correct name is “Tejas Ranganath.”</p><p>The online version of this article has been corrected accordingly.</p><p>We apologize for this error.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"8 10","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.71092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149084091","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}