Complexity最新文献

{"title":"Nonlinear Dynamics and Coexistence of Attractors of a New Jerk-Modified Rayleigh Oscillator","authors":"H. S. Kinhoégbè,&nbsp;L. A. Hinvi,&nbsp;A. A. Koukpémèdji,&nbsp;C. H. Miwadinou,&nbsp;V. A. Monwanou,&nbsp;J. B. Chabi Orou","doi":"10.1155/cplx/2733615","DOIUrl":"https://doi.org/10.1155/cplx/2733615","url":null,"abstract":"<p>Jerk models (the time derivative of acceleration) in nonlinear dynamics provide the mathematical framework necessary to generate deterministic chaos in autonomous systems. This article investigates deterministic chaos in the simplified Selkov model in the absence of external excitation. Specifically, this work studies the nonlinear dynamics, the transition to chaos, and the coexistence of attractors in a new jerk-modified Rayleigh oscillator derived from a Rayleigh oscillator originating from the Selkov system. By applying Tikhonov’s theorem to the Selkov model, the equation of the modified autonomous Rayleigh oscillator is determined. Through conversion, the equation of a new jerk-modified Rayleigh oscillator is obtained, and the fixed points of this new system are determined and then analyzed. The emergence of complex phenomena is studied through numerical simulations based on the direct integration of the system via the fourth-order Runge–Kutta method. The influence of system parameters on the transition to chaos and the coexistence of attractors is studied using parametric diagrams, attraction basins, bifurcation diagrams, the Lyapunov exponent, time series, and phase portraits. Thus, the parameters that promote and those that prevent the appearance of chaotic dynamics and the coexistence of attractors are identified. The autonomous-modified jerk-Rayleigh oscillator is implemented in OrCAD PSpice software to confirm the numerical simulation results. Finally, a linear controller is proposed to eliminate chaotic dynamics and the coexistence of attractors from this new jerk-modified Rayleigh oscillator.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/2733615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Centroid-SAM2: A Minimally Supervised Framework for Automated Tongue Image Segmentation in Traditional Chinese Medicine","authors":"Linjing Peng,&nbsp;Nan Li,&nbsp;Lili Liu,&nbsp;Hengyi Tian,&nbsp;Lifeng Dong,&nbsp;Jianbin Guo,&nbsp;Yiqing Liu,&nbsp;Yuping Zhao","doi":"10.1155/cplx/4888409","DOIUrl":"https://doi.org/10.1155/cplx/4888409","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Tongue image segmentation is fundamental for automated tongue diagnosis in Traditional Chinese Medicine (TCM). Existing deep learning approaches suffer from heavy reliance on manual annotation and limited adaptability to annotation-scarce settings, resulting in suboptimal segmentation performance and poor generalization across diverse clinical environments. This study proposes a novel minimally supervised framework. In this approach, the coarse segmentation stage employs lightweight supervised training with limited annotations, while the fine segmentation stage achieves superior accuracy through fully unsupervised, zero-shot inference leveraging SAM2.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We developed the Centroid-SAM2 model, a minimally supervised tongue image segmentation framework. The first stage employs a coarse segmentation model fine-tuned on 120 annotated images from an independent public dataset, while the second stage leverages the zero-shot capabilities of SAM2 with no labeled data for training or inference; annotations on the target datasets are used solely for evaluation. The approach integrates DeepLabV3_ResNet50 for initial coarse segmentation, followed by a novel centroid coordinate algorithm based on image moments to automatically extract precise guidance points. These centroid coordinates serve as adaptive prompts for the SAM2 model, enabling effective attention guidance in annotation-free segmentation tasks.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Comprehensive experiments across three distinct tongue image datasets demonstrated that Centroid-SAM2 significantly outperformed traditional supervised methods and other minimally supervised approaches. The model achieved exceptional performance with 98.21% mIoU, 98.92% accuracy, 99.73% recall, and 99.32% F1-score on Dataset 1, with consistently high performance maintained across Dataset 2 and Dataset 3. Comparative analysis of different SAM2 model scales revealed that sam2.1-hiera_small provided optimal performance with minimal edge artifacts while maintaining computational efficiency.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The Centroid-SAM2 model represents a significant advancement in minimally supervised medical image segmentation, substantially reducing dependency on manual effort by confining labeling requirements to a small independent dataset, while achieving superior accuracy in tongue segmentation tasks. This innovative approach addresses the critical challenge of annotation scarcity in medical imaging, offering significant pra","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4888409","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk–Return Dynamics and Volatility Connectedness of ESG-Aligned Assets: Extant Evidence, Patterns, and Inquiries","authors":"Laxman Tandan,&nbsp;Rudra P. Pradhan,&nbsp;Bikash Rana","doi":"10.1155/cplx/3038268","DOIUrl":"https://doi.org/10.1155/cplx/3038268","url":null,"abstract":"<p>The advancement of ESG-aligned assets has increased attention in comprehending their risk–return dynamics and volatility behavior in the financial market; however, existing research provides fragmented and mixed evidence, suggesting the necessity of an integrated synthesis. This study reviews the prior knowledge to consolidate and critically evaluate the risk–return dynamics and volatility characteristics of ESG-aligned assets. Using a structured SPAR-4 SLR approach, 78 peer-reviewed published papers from 2015 to 2025 were retrieved from Scopus and Web of Science. The review employs descriptive bibliometric techniques and thematic assessment to synthesize the current literature. The findings identify four major interdependent themes: volatility connectedness, environment/climate risks, diversification strategies, and ESG sentiment. Overall, ESG-aligned assets often provide diversification and resilience benefits, but the direction and magnitude of these benefits rely on asset class, market development, regulatory setting, information quality, and crisis regime. The study synthesizes fragmented evidence and identifies research gaps while offering theoretical, practical, and policy insights for ESG asset pricing and sustainable finance research.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3038268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multiobjective Optimization Framework for Strategic Airport Capacity Planning Under Policy-Driven Demand Scenarios","authors":"Ibrahim M. Hezam","doi":"10.1155/cplx/6737547","DOIUrl":"https://doi.org/10.1155/cplx/6737547","url":null,"abstract":"<p>Rapid passenger-demand growth, budget constraints, and large-scale events create substantial challenges for long-term airport capacity planning. This study develops a scenario-based multiperiod multiobjective mixed-integer linear programming framework for strategic airport capacity planning under alternative policy-driven demand conditions. The model jointly determines continuous component-level expansion and discrete infrastructure projects while explicitly representing terminal, runway, and gate capacities. Investment strategies are evaluated in terms of present-value cost, unmet passenger demand, component-level congestion pressure, and reserve-capacity shortfall. The framework was implemented in YALMIP under MATLAB R2026a and applied to four major Saudi airports over the 2026–2034 planning horizon. Six scenarios represent moderate and high demand growth, constrained funding, reserve-oriented planning, pilgrimage demand pressure, and FIFA World Cup 2034 readiness. The scenarios are deterministic, independent, and nonprobabilistic. Lexicographic objective normalization, systematic weight analysis, and parameter-sensitivity experiments are used to evaluate the stability of the resulting plans. Under moderate growth, forecast demand can be accommodated with a present-value investment of 24.900 billion SAR and no unmet demand. Under sustained high growth, however, conventional project options and constrained budgets lead to substantial congestion and capacity shortfalls. Under the assumed World Cup demand multipliers, project catalogue, budget conditions, and 10% reserve requirement, the model identifies a feasible 2034 capacity plan requiring a present-value investment of 102.373 billion SAR. This value should be interpreted as a model-based planning estimate under the specified assumptions rather than as a forecast of actual national event-readiness expenditure. The framework provides a structured basis for comparing phased airport-capacity expansion strategies under alternative demand and policy conditions.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/6737547","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On QSPR Modeling and SAW-Based Ranking of Laryngeal Cancer Drugs Using Temperature-Based Topological Indices and Support Vector Regression","authors":"Nazek Alessa,&nbsp;Hasnain Hayat,&nbsp;Muhammad Kamran Siddiqui,&nbsp;Samuel Asefa Fufa","doi":"10.1155/cplx/1912298","DOIUrl":"https://doi.org/10.1155/cplx/1912298","url":null,"abstract":"<p>QSPR modeling offers an effective tool for predicting the physicochemical properties of pharmaceutical molecules by applying molecular descriptors. In this research paper, a new QSPR method based on the temperature-based topological indices in graph theory is presented for analyzing selected drugs that are relevant to laryngeal cancer. Graph theory is used as a mathematical tool in representing the molecular structure and extracting structural information from molecular graphs. New temperature-based topological indices are introduced as molecular descriptors in order to extract structural and thermal properties of the molecules. The temperature-based topological descriptors have been used in conjunction with a support vector regression algorithm to predict various physicochemical properties of the drugs. According to the obtained results, there was a reasonable agreement between the experimentally determined values and predicted ones. Hence, the ability of the proposed molecular descriptors in capturing structural information was revealed. Moreover, a mathematical ranking of the drugs based on their physicochemical properties and calculated molecular descriptors is carried out through a simple additive weighting (SAW) technique. Also, the WASPAS technique has been used for obtaining the hybrid multicriteria ranking, which will be used for comparing purposes, whereas the linear regression technique has been applied as a basic predictive model. It is important to note that the obtained SAW ranking was a structural property–based one and should not be considered in terms of therapeutic effect.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/1912298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-UAV Cooperative Environmental Awareness Method via Distributed Information Fusion","authors":"Cheng Qian,&nbsp;Bin Fu","doi":"10.1155/cplx/1855869","DOIUrl":"https://doi.org/10.1155/cplx/1855869","url":null,"abstract":"<p>This paper proposes a distributed information-fusion framework for cooperative environmental awareness in multi-UAV systems. The framework addresses limited individual sensing coverage and incomplete, spatially discontinuous observations in cluttered or communication-constrained scenarios by integrating a UAV control model, a directional perception model, and a feature-level fusion architecture. Salient features from multiple platforms are extracted, normalized for translation, rotation, and scale, and matched to generate a consistent global map. Simulation results show that the proposed method improves situational consistency, reduces redundant data transmission, and enhances flight safety in unknown environments. These results support multi-UAV applications in emergency response, environmental monitoring, and large-area exploration.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/1855869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and Complexity Analysis of Fuzzy-Fractional Chaotic Systems Using Deep Neural Networks","authors":"Shamaila Waheed,&nbsp;Mubashir Qayyum,&nbsp;Aiedh Mrisi Alharthi,&nbsp;Syed Tauseef Saeed,&nbsp;Gilbert Chambashi","doi":"10.1155/cplx/5409055","DOIUrl":"https://doi.org/10.1155/cplx/5409055","url":null,"abstract":"<p>Nonlinear dynamical systems exhibiting chaos, memory and uncertainty effects play a vital role in the modeling of complex phenomena in science and engineering. Due to the rapid growing of development in machine learning and artificial intelligence, data-driven methods have been widely used for predicting and analysing nonlinear dynamical systems. Neural network-based architectures have demonstrated strong potential in learning hidden dynamics directly from time-series data. In this study, a data-driven framework is proposed for modeling and analysis of fuzzy-fractional chaotic systems with special focus on Lorenz, Chen, and Burke–Shaw type models. Uncertainty and imprecision in system parameters are incorporated through triangular fuzzy numbers, leading to fuzzy-fractional formulations capable of capturing richer dynamical behaviours. Time-series trajectories are initially generated using an explicit fractional-order Runge–Kutta scheme and subsequently employed to train an autoregressive residual multilayer perceptron to learn the underlying system evolution directly from data. The proposed learning architecture effectively produces long-term dynamics of considered systems. To quantify the performance of the proposed residual multilayer perceptron, a comprehensive dynamical analysis is conducted through computation of the full Lyapunov spectrum and Kaplan–Yorke dimension, providing insights into sensitivity to initial conditions, attractor dimensionality, and emergent chaotic behaviour. The results demonstrate that proposed framework offers a robust and scalable approach for capturing, analyzing, and quantifying complexity in fuzzy-fractional chaotic systems, thereby contributing to the understanding of uncertainty-driven dynamics in nonlinear complex systems. Notably, hyperchaotic behaviour characterised by two positive Lyapunov exponents is detected in the fuzzy-fractional Chen system under six out of nine parameter configurations. In fuzzy-fractional Burke–Shaw system, hyperchaos is also observed for some combinations of fractional-order and fuzzy cut level.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5409055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Macroeconomic Uncertainty and Nonlinear Information Flow in Stock-Return Predictability","authors":"Shiyi Wang,&nbsp;Liyi Liu,&nbsp;Shan Chen","doi":"10.1155/cplx/3856796","DOIUrl":"https://doi.org/10.1155/cplx/3856796","url":null,"abstract":"<p>A central problem in cross-sectional stock-return prediction is how to balance two competing forecasts built from the same firm characteristics: a stable long-horizon forecast that averages predictive signals over many years and a responsive short-horizon forecast that adapts quickly to recent market conditions. Existing combination rules set this balance using purely statistical criteria or a linear projection on macroeconomic uncertainty, implicitly assuming that uncertainty shifts the optimal balance by the same amount in all market states. This study examines whether uncertainty instead carries nonlinear and state-dependent information about the optimal balance, and whether exploiting that information improves out-of-sample prediction. Using monthly returns and 94 firm characteristics for U.S. common stocks from January 1990 to December 2025, together with five uncertainty indices covering policy, financial, real, macroeconomic, and market-implied uncertainty, we measure nonlinear and directional dependence with mutual information and transfer entropy and develop a nearest-neighbor forecasting rule, MI–kNN–LASSO, which sets the balance by comparing the current uncertainty environment with historically similar states. All five indices relate to the optimal balance more strongly than linear correlations suggest, with macroeconomic uncertainty providing the most reliable predictive signal. The proposed rule forecasts the combination state far more accurately than the linear benchmark and earns a long–short return of 63 basis points per month with a smaller maximum drawdown. Our method offers investors an interpretable and adaptive way to combine return forecasts.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/3856796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Rational Agents to Learning Agents: A Structured Review and Conceptual Framework for MARL in Economic Modeling","authors":"Yiwei Wang","doi":"10.1155/cplx/4688591","DOIUrl":"https://doi.org/10.1155/cplx/4688591","url":null,"abstract":"<p>This paper provides a systematic review of the emerging literature on multiagent reinforcement learning (MARL) in economics. The review is motivated by the rapid expansion of MARL methods in computational modeling and the lack of a clear framework that connects this literature to established economic approaches. The paper first introduces the shared dynamic structure underlying MARL and economic decision problems, including Markov decision processes and Bellman equations, and clarifies the distinction between adaptive agents and rule-based agents. It then organizes existing applications of MARL in four domains: macroeconomics, finance, market design, and behavioral economics. Across these domains, the review identifies the main research themes, common modeling choices, and current limitations. A central argument of the paper is that progress in this field depends not only on stronger algorithms but also on clearer standards for economic interpretation, model design, and empirical credibility. To address this issue, the paper develops a trustworthiness-centered evaluation perspective and outlines an operational architecture for applying MARL in economic research. The contribution is conceptual rather than algorithmic: The paper offers a shared analytical vocabulary, a structured map of the literature, and a roadmap for future work at the intersection of economics and computer science.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4688591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Textbooks Through Concept Network Analysis","authors":"Xiang Cao,&nbsp;Jiachen Yu,&nbsp;Jinshan Wu","doi":"10.1155/cplx/5250722","DOIUrl":"https://doi.org/10.1155/cplx/5250722","url":null,"abstract":"<p>Textbooks serve as the primary basis for instructional activities, with their knowledge organization directly shaping teaching and learning pathways. We establish a framework for quantitative textbook evaluation based on concept network analysis and apply it to five elementary mathematics textbooks. Concept networks are constructed from each textbook, their topological properties are analyzed, and an information spreading model is applied to evaluate learning efficiency. Three networks exhibit high modularity and long path lengths, with influential nodes centered on observation-based learning and computational procedures. The other two exhibit high density, short path lengths, and high clustering, with influential nodes centered on general mathematical thinking such as abstraction and deductive reasoning. The spreading model demonstrates that textbooks organized around advanced knowledge achieve substantially higher efficiency. These findings suggest concept network analysis can serve as an effective tool for textbook evaluation.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/5250722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}