Results in Control and Optimization最新文献

{"title":"Sustainable wind farm layout design for maximizing power output and reducing environmental impact","authors":"Khamiss Cheikh ,&nbsp;EL Mostapha Boudi ,&nbsp;Rabi Rabi ,&nbsp;Hamza Mokhliss","doi":"10.1016/j.rico.2026.100664","DOIUrl":"10.1016/j.rico.2026.100664","url":null,"abstract":"<div><div>Wind farm layout design continues to face methodological constraints that limit its applicability under realistic operating conditions. Existing approaches frequently rely on single-objective formulations that prioritize either energy maximization or wake-loss reduction, thereby failing to capture the interdependent trade-offs among power generation, turbulence intensity, and wake-induced performance degradation. In addition, widely adopted wake models often use simplified aerodynamic representations that overlook turbine–turbine coupling effects, while deterministic wind-field assumptions ignore the stochastic variability in wind speed and direction that critically influences wake propagation. These limitations underscore the need for a more comprehensive and physically grounded optimization strategy. This study proposes a tailored multi-objective optimization framework that integrates analytical wake modeling with stochastic environmental characterization to identify efficient turbine placements within the farm boundary. The method concurrently optimizes power output, turbulence attenuation, and wake-related energy deficits while enforcing spatial and operational constraints. Numerical evaluations demonstrate marked performance improvements relative to baseline configurations. Turbines situated in favorable aerodynamic regions (<em>T4</em> and <em>T5</em>) achieve power outputs of <em>1.84–1.89 MW</em>, representing an increase of up to <em>72%</em> compared to downstream turbines subjected to wake interference (<em>1.03–1.13 MW</em>). Turbulence intensity decreases by more than <em>55%</em> (<em>1.20–1.28</em> versus <em>2.58–2.81</em>), and wake-related energy losses are reduced by over <em>60%</em> (0<em>.0065–0.0072</em> versus <em>0.013–0.017</em>). These quantitative gains confirm the efficacy of the proposed optimization framework and highlight its potential for scalability, enhanced aerodynamic fidelity, and integration into future large-scale wind-farm planning and operational decision-support systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100664"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077459","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":"Enhanced relaxation-based local stabilization of T-S fuzzy systems: Achieving a simultaneous reduction in conservatism and complexity","authors":"Sung Hyun Kim","doi":"10.1016/j.rico.2026.100660","DOIUrl":"10.1016/j.rico.2026.100660","url":null,"abstract":"<div><div>This paper proposes an enhanced relaxation-based local stabilization framework for continuous-time T–S fuzzy systems that simultaneously reduces conservatism and computational complexity. In contrast to existing approaches, the proposed method eliminates the need for a priori assumptions or static transformations of the time derivatives of fuzzy basis functions, and enables a complete local stabilization procedure to be carried out entirely within the LMI framework. Moreover, by introducing a full row-rank canonical selection matrix, the number of slack variables is significantly reduced, thereby improving computational efficiency without sacrificing stability performance. Consequently, the resulting relaxation framework yields less conservative stabilization conditions and facilitates efficient controller synthesis for high-dimensional fuzzy systems. Finally, the effectiveness of the proposed method is demonstrated through two illustrative examples (i.e., cart-pendulum and mass–spring-damper examples), which show improved <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance and substantial reductions in decision variables.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100660"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173487","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":"Phase-dependent nonlinear MPC for stair climbing: Edge-pivot control with a double-pendulum model","authors":"Carlos Raymundo,&nbsp;Gustavo Pérez-Zuñiga,&nbsp;Ivan Yupanqui","doi":"10.1016/j.rico.2026.100675","DOIUrl":"10.1016/j.rico.2026.100675","url":null,"abstract":"<div><div>This paper develops and validates optimal control for a double-pendulum and a hybrid switching controller for a wheel-based stair-climbing device (SCD). An energy-based linear and nonlinear model is derived and used to design LQR, observer-based state feedback, linear MPC, and nonlinear MPC (NMPC). The resulting nonlinear optimal control problems (OCPs), defined as nonlinear programs (NLPs), are solved with a numerical solver using a Real-Time Iteration (RTI) scheme, allowing NMPC to enforce the full nonlinear dynamics and state/input constraints. Under identical tests, the implemented NMPC best drives both links to upright equilibrium with the lowest tracking error for comparable effort. The implemented NMPC is then embedded in a phase-dependent switch where the LQR governs the nominal rolling, while at the critical edge pivot modeled as an inverted double-pendulum triggers the NMPC via hysteretic distance guards with contact confirmation and dwell time; after capture, the controller returns to LQR. This yields reliable, chatter-free switching and improved ascent/descent performance while saving energy.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100675"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396384","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":"On the chaotic systems of attraction with fractional operators in a novel Lorenz system","authors":"Atul Kumar ,&nbsp;Hambeer Singh ,&nbsp;Salah Boulaaras ,&nbsp;Kamal Shah ,&nbsp;Thabet Abdeljawad","doi":"10.1016/j.rico.2026.100678","DOIUrl":"10.1016/j.rico.2026.100678","url":null,"abstract":"<div><div>In this research, a novel variant model of the classical Lorenz system is proposed by reformulating both the classical and fractional-order Lorenz systems through a new framework based on piecewise fractional derivatives. The resulting piecewise Lorenz system is formulated as a nonlinear system of differential operators exhibiting rich and complex dynamical behaviors induced by the piecewise structure. The proposed model is developed within the frameworks of the Caputo fractional derivative, the Atangana–Baleanu fractional derivative, and the Caputo–Fabrizio fractional derivative. A rigorous qualitative analysis is carried out to establish the existence and uniqueness of solutions for the modified piecewise Lorenz system. Furthermore, the dynamical and chaotic properties of the system are investigated through numerical approximations based on the Newton interpolation formula. Numerical simulations and graphical illustrations demonstrate the effectiveness and accuracy of the proposed numerical scheme and reveal the influence of fractional orders and system parameters on the system dynamics. In particular, the system exhibits crossover behavior and chaotic dynamics characterized by the coexistence of two strange attractors, highlighting significant differences from the classical Lorenz system.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100678"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396391","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 generalized Vidale–Wolfe model on existing and new customers advertising strategy in a segmented market","authors":"Onamy Ramdinpuii ,&nbsp;Kuldeep Chaudhary ,&nbsp;Surbhi Gupta ,&nbsp;Shivani Bali","doi":"10.1016/j.rico.2026.100673","DOIUrl":"10.1016/j.rico.2026.100673","url":null,"abstract":"<div><div>Business firms and companies are constantly adopting the concept of market segmentation, which plays an important role in the promotion of a product. Additionally, advertising is another component that strengthens the company’s communication with customers. To have effective marketing strategies, the implementation of independent advertising strategies for each segmented market is important. This paper deals with an optimal control problem that aims to obtain a dynamic advertising policy for new customers as well as minimize the decay rate for existing customers in a segment-specific market. We will an derive explicit optimal dynamic advertising efforts policy using Pontryagin’s maximum principle. The analysis gives a deep insight into how the advertising effort should be planned by the decision-makers, designing strategies that maximize long-term profitability while effectively controlling advertising costs. The effectiveness of the suggested strategy is supported by numerical examples, along with parameter estimation to estimate the value of certain parameters.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100673"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396392","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":"Modelling lymphatic filariasis dynamics using Levenberg–Marquardt algorithm-artificial neural networks","authors":"Mussa A. Stephano ,&nbsp;John N. Mlyahilu ,&nbsp;Il Hyo Jung","doi":"10.1016/j.rico.2026.100659","DOIUrl":"10.1016/j.rico.2026.100659","url":null,"abstract":"<div><div>This paper introduces a hybrid Levenberg–Marquard-Artificial Neural Network (LMA-ANN) framework for modeling the complex transmission dynamics of lymphatic filariasis (LF), a debilitating vector-borne neglected tropical disease. The methodology addresses key challenges in data-driven epidemiological forecasting by combining the fast convergence properties of the Levenberg–Marquardt optimization algorithm with the universal function approximation capability of neural networks. We evaluate the proposed framework against four established neural architectures such as Multilayer Perceptron (MLP), Fully Connected Neural Network (FCNN), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) using both pristine and Gaussian noise-augmented synthetic datasets generated from a compartmental epidemiological model solved with a high-fidelity Runge–Kutta method. Results demonstrate that the LMA-ANN achieves superior predictive accuracy, with the lowest error metrics of <span><math><mrow><mi>M</mi><mi>A</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>029</mn><mo>,</mo><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>039</mn><mo>,</mo><mi>M</mi><mi>S</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>0015</mn></mrow></math></span> and highest coefficient of determination of <span><math><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>990</mn></mrow></math></span> on noise-augmented data, while maintaining computational efficiency with the shortest training of <span><math><mrow><mn>87</mn><mo>.</mo><mn>4</mn><mspace></mspace><mi>s</mi></mrow></math></span> and inference of <span><math><mrow><mn>2</mn><mo>.</mo><mn>9</mn><mspace></mspace><mtext>ms</mtext></mrow></math></span> times. Crucially, the CNN and RNN architectures exhibited worst performance degradation on the noise-augmented dataset, yielding negative <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> values of <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>15</mn></mrow></math></span> and <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>42</mn></mrow></math></span> respectively, indicating predictions worse than a simple mean model. This highlights a critical limitation of complex architectures when trained on limited, noisy epidemiological data. The study provides two principal contributions: (1) a robust, computationally efficient LMA-ANN framework that accurately captures LF dynamics under realistic data constraints, and (2) evidence-based guidance for model selection in epidemiological applications, emphasizing that architectural complexity must be carefully matched with data quality and quantity. These findings advance computational methods for infectious disease modeling and offer a generalizable tool for public health decision-making in resource-limited settings.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100659"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977842","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":"Analysing the effects of dual time delays and terror funding class in terrorism dynamics","authors":"Annesha Sarmah ,&nbsp;Kaushik Dehingia ,&nbsp;Purnendu Sardar ,&nbsp;Anusmita Das ,&nbsp;Hemanta kr. Sarmah ,&nbsp;Santosh Kumar Choudhary","doi":"10.1016/j.rico.2026.100662","DOIUrl":"10.1016/j.rico.2026.100662","url":null,"abstract":"<div><div>In this paper, we develop a novel five-compartment terrorism dynamics model that explicitly incorporates a terror funding class, thereby capturing the critical role of financial resources in sustaining recruitment, logistics, and operational activities. To better reflect real-world processes, the model introduces two discrete time delays: <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>, representing the indoctrination period required for susceptible individuals to become terrorists, and <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>, denoting the lag associated with transferring terrorists to the recovered or quarantined classes. The main contributions of this work include: (i) the formulation of a funding-integrated terrorism model with dual delays; (ii) a complete mathematical analysis of positivity, boundedness, and equilibrium stability; (iii) derivation of the basic reproduction number <span><math><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> and a sensitivity analysis identifying the parameters that most strongly influence terrorism persistence; and (iv) a rigorous investigation of delay-induced destabilisation and Hopf bifurcation. For the non-delayed system, we establish conditions ensuring the existence and local stability of the terror-free equilibrium when <span><math><mrow><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&lt;</mo><mn>1</mn></mrow></math></span> and the terror-persistent equilibrium when <span><math><mrow><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&gt;</mo><mn>1</mn></mrow></math></span>. For the delayed system, we demonstrate that increasing either <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> or <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> beyond their respective critical thresholds leads to Hopf bifurcations and sustained oscillations, representing recurrent waves of terrorist activity. Numerical simulations are provided to validate the analytical results. Overall, the study offers insight into how the speed of radicalisation, operational delays, and financial resources interact to shape terrorism dynamics, with potential implications for the design of more effective counter-terrorism policies.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100662"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077458","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":"Machine-learning-enhanced glowworm swarm optimization for energy-efficient multi-hop routing in wireless sensor networks","authors":"Namit Gupta ,&nbsp;Abu Bakar bin Abdul Hamid ,&nbsp;Abu Bakar Bin Mahat ,&nbsp;Adesh Kumar","doi":"10.1016/j.rico.2026.100667","DOIUrl":"10.1016/j.rico.2026.100667","url":null,"abstract":"<div><div>Energy-efficient wireless sensor networks (WSNs) are critical for modern intelligent applications, yet maintaining balanced battery power across the network remains a persistent challenge. Numerous algorithms have been proposed to address this issue, but notable research gaps still exist. This study introduces a novel multi-hop routing framework designed to enhance energy efficiency and prolong network lifetime. The framework integrates six key components: a network model, a radio and energy model, cluster deployment using a low-energy adaptive clustering hierarchy (LEACH), cluster-head selection via a glowworm swarm optimization algorithm, multi-hop routing through a Taylor-based cat-salp swarm method, and machine-learning driven analysis employing both k-means and hierarchical clustering. The simulation results demonstrate superior performance over existing state-of-the-art approaches, achieving higher total residual energy, reduced end-to-end delay, lower packet drop rates, improved packet delivery ratio, and greater overall throughput. Hierarchical clustering with Ward linkage achieved an accuracy of 96.76% with an R² value of 0.9852 for packet drop and an accuracy of 97.37% with an R² value of 0.9831 for network throughput, while K-means clustering attained an accuracy of 96.25% with an R² value of 0.9725 for packet delivery ratio. The novelty of this work is the synergistic integration of optimization-assisted machine learning clustering with adaptive multi-hop routing, enabling dynamic and energy-aware cluster head selection while explicitly minimizing both intra- and inter-cluster communication overhead, an aspect largely unaddressed in conventional WSN protocols.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100667"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173474","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":"Enhancing renewable energy utilization through solar, wind, and electric vehicles in the grid using a chaotic-based prairie dog optimization algorithm","authors":"Ayan Das Sarkar ,&nbsp;Provas Kumar Roy ,&nbsp;Barun Mandal ,&nbsp;Ghanshyam G. Tejani ,&nbsp;Seyed Jalaleddin Mousavirad","doi":"10.1016/j.rico.2025.100646","DOIUrl":"10.1016/j.rico.2025.100646","url":null,"abstract":"<div><div>This study aims to determine the most effective operational strategy for economic load dispatch (ELD). The practical ELD problem can be difficult to solve because of its non-smooth cost function and nonlinear constraints; specifically, electric power generation’s nonlinear multi-objective economic emission dispatch (EED) problem with valve point loading is solved using the prairie dog optimization algorithm-based optimization (PDO). The problem considers nonlinear generator aspects such as valve point effect, ramp rate limits, and restricted operating zones. The PDO technique identifies the optimal solution without requiring any prior knowledge of the gradient of the objective function. The application of the PDO algorithm to solve nonlinear ELD problems appears to be an effective and reliable optimization technique. Three test cases are considered. For example, 40 units with losses (thermal units and renewable energy), 140 units (renewable energy), and 160 units (thermal units and renewable energy) are used for executing and evaluating the suggested algorithm. The outcomes demonstrate the suggested algorithm’s potential and efficacy in comparison to other alternative techniques, and the suggested approach outperforms other established algorithms in terms of proficiency and robustness, as demonstrated by numerical data.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100646"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792048","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":"Optimizing epidemic control: Nash game approach to stochastic modeling with Brownian motion","authors":"Md. Abdullah Bin Masud ,&nbsp;Sharmina Rahman ,&nbsp;Faijun Nesa Shimi ,&nbsp;Mostak Ahmed ,&nbsp;Rathindra Chandra Gope","doi":"10.1016/j.rico.2026.100657","DOIUrl":"10.1016/j.rico.2026.100657","url":null,"abstract":"<div><div>This research expands upon stochastic modeling for COVID-19 management by incorporating Nash game theory to optimize control strategies for disease transmission. Building on our original model, which has integrated Brownian motion and nonlinear dynamics to enhance diagnosis and isolation procedures, we now apply Nash game theory to explore the interactions between multiple control variables. Using Pontryagin’s Maximum Principle for theoretical analysis and MATLAB and Python for numerical simulations, we demonstrate that Nash control offers a more practical approach than traditional game theory for balancing interventions. The model’s performance, validated with Worldometer data, achieves low Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), underscoring its high predictive accuracy. Our findings suggest that Nash control provides a superior framework for real-time epidemic management by optimizing disease control policies, particularly when coordinating antiviral treatments and isolation measures. This work highlights the advantages of Nash-based strategies in developing robust and adaptive epidemic management systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100657"},"PeriodicalIF":3.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977841","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}