alexandria engineering journal最新文献

{"title":"Biosorption of methylene blue from industrial wastewater using silicon dioxide nanoparticles and Cladophora glomerata","authors":"Alaa M. Metwally ,&nbsp;Samia A.A. Aly ,&nbsp;Sarah O. Makled ,&nbsp;Amr M.S. Abdelkader","doi":"10.1016/j.aej.2025.09.004","DOIUrl":"10.1016/j.aej.2025.09.004","url":null,"abstract":"<div><div>Methylene Blue is a common pollutant in industrial wastewater, posing environmental risks, impacting aquatic ecosystems, and degrading the aesthetic quality of water. Biosorption has emerged as an effective alternative for wastewater treatment, utilizing various absorbents, including algae, for the removal of dyes. This study investigates the biosorption efficiency of Methylene Blue using <em>Cladophora glomerata</em> macroalgae and silicon dioxide nanoparticles, which were characterized using SEM and FTIR. Key parameters, including adsorbent dosage, pH, and contact time, were evaluated to optimize the removal process. Under optimal conditions (temperature: 20 ± 2 °C, stirring speed: 300 rpm, contact time: 60 min, pH: 5, initial dye concentration: 20 mg/L, and adsorbent dose: 1.3 g/L), silicon dioxide nanoparticles demonstrated nearly 100 % dye removal. <em>Cladophora glomerata</em> achieved 95.55 % removal within 50 min at a dosage of 1.0 g/L. A hybrid approach combining both adsorbents reached similar removal efficiency in 50 min at a lower dose of 0.6 g/L. Kinetic analysis revealed that the biosorption process followed the pseudo-second-order non-linear model, exhibiting high correlation coefficients (average R² = 0.996, 0.997, and 0.999). The biosorption data were well described by the Elovich kinetic model (R² &gt; 0.9) and fitted both the Langmuir and the Freundlich isotherms, indicating a good fit of the experimental data, confirming monolayer adsorption on heterogeneous surfaces. These findings suggest that <em>Cladophora glomerata</em>, a macroalga, and silicon dioxide nanoparticles are efficient, cost-effective, and environmentally friendly adsorbents for removing Methylene Blue from industrial wastewater.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 115-138"},"PeriodicalIF":6.8,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Few-shot agricultural disease detection method using contextual attention generation","authors":"Xin Ning ,&nbsp;Shanwei Gao ,&nbsp;Jentang Liu ,&nbsp;Long Cheng ,&nbsp;Yugui Zhang","doi":"10.1016/j.aej.2025.08.045","DOIUrl":"10.1016/j.aej.2025.08.045","url":null,"abstract":"<div><div>Agricultural diseases are a problem on a global scale. Developing efficient methods for detecting various types of plant diseases is of great significance for boosting the yield of economic crops. Given the characteristics of limited samples and class imbalance among different plant disease types, this study proposes a generative few-shot agricultural disease detection method based on a contextual attention mechanism. Our approach constrains contextual information in layout positions of different categories within images, enhancing the model's ability to understand categorical spatial relationships and achieving more precise disease localization; Subsequently, we design a semantic feature vector fusion method that integrates disease characteristics with leaf features in generated images through attention mechanisms, ensuring high visual fidelity; Furthermore, we introduce a generative model-based augmentation paradigm that utilizes feature consistency for data expansion, effectively enlarging plant disease datasets. Comprehensive experiments validate our method on two datasets using multiple state-of-the-art object detection models. Results demonstrate an average improvement of 12.9 % across these models on the two datasets. This framework significantly enhances model generalization for rare categories and imbalanced disease data recognition, providing a robust solution to data scarcity challenges in plant disease object detection.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 101-114"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning optimization for vocational literacy education evaluation: A big data-powered decision support system","authors":"Hong Li","doi":"10.1016/j.aej.2025.08.029","DOIUrl":"10.1016/j.aej.2025.08.029","url":null,"abstract":"<div><div>This paper is motivated by the urgent requirement for creative solutions to address the challenges faced by vocational colleges in China’s rapidly advancing higher education system. It aims to use big data and data mining to improve vocational education and develop students’ professional characteristics. This study developed a comprehensive evaluation system for vocational education by using a decision support system (DSS) and data mining approaches based on big data analysis. The development is carried out in several stages. First, a complete DSS-based evaluation index system is developed by using large-scale data analysis. For this purpose, eight indicators were chosen to test students’ vocational literacy and create DSS and parameter matrices. Secondly, it uses the technique for order of preference by similarity to the ideal solution (TOPSIS) approach to analyze the results for each indicator, offering a solid foundation for decision-making. Thirdly, it uses regression analysis through the logistic regression model to investigate the particular features that impact students’ vocational literacy in vocational schools. Fourthly, the classification analysis is carried out to predict and analyze the vocational literacy level of vocational college students by using support vector machine (SVM), logistic regression, and AdaBoost. According to the assessment findings, 57% of students are judged competent or extremely competent, indicating that the majority have the essential vocational literacy for work. However, a comparison of students’ self-perceptions with enterprise ratings needs to be more consistent. Students tend to rank their vocational literacy better, with ratings around 4.0, whilst enterprise assessments linger around 3.6 points.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"129 ","pages":"Pages 1258-1271"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145026342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel robust control for permanent magnet synchronous motor integrating deadbeat predictive current control and sliding mode observer","authors":"Xiaozhuo Xu ,&nbsp;Liangjie Wang ,&nbsp;Zan Zhang ,&nbsp;Zhonghua Wu","doi":"10.1016/j.aej.2025.08.057","DOIUrl":"10.1016/j.aej.2025.08.057","url":null,"abstract":"<div><div>To address parameter mismatch and external load disturbance in permanent magnet synchronous motor (PMSM), a novel robust control for PMSM integrating deadbeat predictive current control (DPCC) and sliding mode observer (SMO) (NRCIDS) is proposed. Firstly, the mathematical models characterized by the PMSM dynamics and DPCC algorithm are derived. Subsequently, the robustness of DPCC against parameter variations is systematically investigated. Secondly, in the speed loop, the load disturbance is compensated by a speed loop disturbance observer. In order to reduce the chattering phenomenon of the conventional SMO, an improved exponential convergence law SMO is adopted. The dynamic response of the speed is improved by this approach, while the chattering phenomenon inherent in traditional SMO is significantly mitigated. Meanwhile, in the current loop, motor parameter disturbances are compensated by a novel terminal SMO. The proposed terminal observer suppresses chattering while it effectively reduces steady-state current error. The speed loop and current loop disturbance observers collaboratively compensate for system disturbances, thereby enhancing overall control performance. Finally, experimental results demonstrate that the proposed control strategy achieves superior performance in terms of dynamic response speed, disturbance suppression, and steady-state accuracy.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 57-67"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy, exergy, environmental, and exergoeconomic (4E) analysis of a fossil fuel power plant with carbon capture unit for a sustainable future","authors":"Tahir Abdul Hussain Ratlamwala ,&nbsp;Khurram Kamal ,&nbsp;Hafsa Javed ,&nbsp;Sheikh Muhammad Ali Haider ,&nbsp;Muhammad Abid ,&nbsp;Sayem Zafar ,&nbsp;Mohammed Alkahtani","doi":"10.1016/j.aej.2025.08.056","DOIUrl":"10.1016/j.aej.2025.08.056","url":null,"abstract":"<div><div>The contribution of fossil fuels to the detrimental trend of global warming is undeniably real. Given the energy sector's heavy reliance on fossil fuels, it is crucial to take necessary actions to mitigate their adverse environmental impact. This study proposes a fossil fuel (natural gas) power plant integrated with a carbon capture unit (CCU) to minimize the associated environmental impacts. A thorough analysis of the system's energy, exergy, environmental, and exergoeconomic aspects (4E) reveals valuable insights into the proposed design. This CCU system captures CO₂ from the combined cycle power plant (CCPP) exhaust and employs it as a working fluid in the Supercritical CO₂ Power Cycle. The system generates 42.4 MW of power, 25.3 MJ/s of heat energy for hot water production, 49.6 MJ/s of heat energy for water desalination, 192.3 kJ/s for space cooling, and medium-pressure (MP) steam with a heat energy of 24.9 MJ/s. The system achieves 50 % energy efficiency and 54 % exergy efficiency, capturing 190.37 kilo metric tons of CO₂ per year. Additionally, the study examines the impact of variations in inputs, including air-fuel ratio, fuel quantity, ambient temperature, and steam temperature at the Heat Recovery Steam Generator (HRSG) outlet, on system efficiencies. 4E analysis reveals that the proposed system is more beneficial than simple power plants with no carbon capture units.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 68-84"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mini-channel heat sink design for solar photovoltaic cooling: Experimental evaluation and performance metrics","authors":"Zouheyr Noui ,&nbsp;Nabil Bessanane ,&nbsp;Mohamed Si Ameur ,&nbsp;Amel Djebara ,&nbsp;Adnan Ibrahim ,&nbsp;Sharul Sham Dol ,&nbsp;Hariam Luqman Azeez","doi":"10.1016/j.aej.2025.09.010","DOIUrl":"10.1016/j.aej.2025.09.010","url":null,"abstract":"<div><div>Effective thermal management in photovoltaic (PV) systems is key to preserving energy efficiency and extending panel lifespan. This study aims to improve PV thermal regulation by introducing a patented S-mini-channel heat sink (SMCHS) designed to overcome fluid maldistribution challenges common in traditional PV cooling configurations. The proposed system consists of 53 minichannels integrated with a triangular header and lateral inlet/outlet design, intending to promote uniform flow distribution under varying operating conditions. On the one hand, experimental results demonstrate significant cooling performance, with surface temperature reductions of 21.48 °C (front) and 35.39 °C (rear) under 800 W/m² solar radiation. The change led to a 1.17 % improvement in electrical efficiency (from 11.42 % to 12.5 %) and a 9.43 % increase in power output, equivalent to a gain of 1.89 W. Additionally, a 4 °C temperature rise in the coolant at a flow rate of 4 L/min confirmed the system's effective heat transfer capacity. On the other hand, a three-dimensional conjugate heat transfer numerical model was validated against the experimental measurements and employed to reinforce flow behavior analyze. The numerical simulations confirmed that an optimal outlet velocity of 0.217 m/s results in a uniform velocity profile across all minichannels, with an average flow velocity of 0.031 m/s per channel. Thus, the SMCHS design ensures consistent thermal performance, enhances energy conversion, and offers promising potential for industrial applications in next-generation PV systems and solar thermal technologies.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 85-100"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fractional calculus approach to analyze physicochemical relaxation processes of charge trapping in organic based nano-photodiodes","authors":"B.-A. Paez-Sierra","doi":"10.1016/j.aej.2025.09.005","DOIUrl":"10.1016/j.aej.2025.09.005","url":null,"abstract":"<div><div>Fractional calculus deals with differentiation and integration of arbitrary real or complex orders. Its application to physicochemical processes in organic-based nano-photodiodes offers a distinct advantage by enabling the explicit characterization of memory effects, phenomena that are often hided in conventional calculus. We present a novel application of fractional calculus to quantify metastable effects in organic nano-photodiodes, revealing temperature-dependent trap states characterized via Mittag-Leffler kinetics. Therefore, the primary analyses focuses on the metastable capacitance, <em>ΔC</em>, polarisation, <em>P</em>, and conductance, <em>G</em>. Although these metastable effects have been reported previously for organic-based transistors. It is remarkable that these effects are also commonly observed in organic-based nano-photodiodes. The model structure consists of a poly(3-hexylthiophene) (<em>P3HT</em>):[6,6]-phenyl-C₆₁-butyric acid methyl ester (<em>PCBM</em>) active layer deposited on a glass substrate coated with indium tin oxide (ITO) and a poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (<em>PEDOT:PSS</em>) buffer layer, with aluminum (Al) serving as the top electrode. Measurements were carried out from 122.0 <em>K</em> to 335.0 <em>K</em>. The trap activation temperature was determined from the dielectric loss (G/ω) measured at a frequency of 1 <em>kHz</em> (f = 2πω), which is well below the cutoff frequency of 650 <em>kHz</em>. The system dynamics were modeled by deriving a fractional differential equation within the Caputo paradigm, with transient solutions expressed as Mittag-Leffler functions ML(α,−t/τ), where α is the fractional order and τ the relaxation time constant. Main findings are: (1) A unique fractional calculus approach was applied to analyze metastability in organic nano-photodiodes, leading to a first-principles derivation of a fractional equation for transient capacitance and polarisation. (2) The unresponsive polarisation between 191.3 and 253.9 <em>K</em> reflects balanced hole–electron recombination rates. (3) Temperature-dependent trap regimes below 191.3 <em>K</em> and above 253.9 <em>K</em> provides a roadmap for optimizing organic photodiodes by tailoring active-layer compositions to suppress recombination in critical temperature ranges.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 47-56"},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diverse bimetallic MOF polymorphs for the degradation of pollutants/antibiotics and quantum dot integration for enhanced WLED performance","authors":"Kasimayan Uma ,&nbsp;Cheng-Han Wu ,&nbsp;Ting-Wei Shen ,&nbsp;Robin Khosla ,&nbsp;Xiu-Jia Guan ,&nbsp;Wei-Kuan Hung ,&nbsp;Zong-Liang Tseng","doi":"10.1016/j.aej.2025.09.006","DOIUrl":"10.1016/j.aej.2025.09.006","url":null,"abstract":"<div><div>A bimetallic composite of cobalt (Co) and nickel (Ni) integrated into a zirconium-based metal-organic framework (ZrMOF) was successfully synthesized via a hydrothermal method for dual-functional applications. The Ni-Co/ZrMOF composite demonstrated good photocatalytic activity in degrading organic pollutants, particularly the antibiotic tetracycline (TC), outperforming Ni/ZrMOF, Co/ZrMOF, and pristine ZrMOF. This enhanced performance was attributed to the synergistic effect of the bimetallic system, which significantly increased the production of reactive oxygen species. Additionally, the integration of Ni-Co/ZrMOFs enabled the fabrication of a white light-emitting diode (WLED) by incorporating green formamidinium lead-bromide perovskite quantum dots (FAPQDs) and red-emitting phosphors powder onto a blue LED chip. The inclusion of FAPQDs into the Ni-Co/ZrMOF framework not only modified its structural properties but also enhanced its chemical stability through a straightforward solution-processing method. The resulting WLED exhibited superior performance, achieving a National Television System Committee (NTSC) color gamut coverage of 126.6 %. Notably, the NTSC coverage achieved in this work surpasses previously reported values, highlighting the excellent performance of the Ni-Co/ZrMOF@FAPQDs composite. This composite exhibits precise color coordinates and significant potential for next-generation WLED applications, further underscoring its versatility in environmental remediation and advanced optoelectronic devices.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 35-46"},"PeriodicalIF":6.8,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and analysis of biomimetic nested lattice structures based on additive manufacturing","authors":"Dongming Li ,&nbsp;Long Guo ,&nbsp;Tongyuan Sun ,&nbsp;Jiasen Si","doi":"10.1016/j.aej.2025.09.009","DOIUrl":"10.1016/j.aej.2025.09.009","url":null,"abstract":"<div><div>There are various hierarchical structures in nature, such as the double-layer wings of a dragonfly, which possess enhanced mechanical properties while also being lightweight. Inspired by the double-layer wings of the dragonfly, this paper adopts bionics and novel hierarchical design concepts to design a single-layer hexagonal crystal lattice SFCC and two double-layer hexagonal crystal lattices DFCC and RFCC. Using the selective laser melting technology (SLM) in additive manufacturing (AM), the AlSi10Mg powder is melted and formed. The mechanical properties and failure mechanisms of these three lattice structures were systematically studied through numerical simulation and compression tests. The strains of them were observed using DIC deformation diagrams. Studies have shown that compared with SFCC, DFCC has a significantly better resistance to deformation in the compressed internal structure. Its <em>EA</em> and <em>SEA</em> have been significantly improved, and it has the optimal overall mechanical properties, verifying the effectiveness of the nested structure. Finally, the mechanical properties of five different diameter ratios of unit cells of DFCC were discussed. Among them, the unit cell with an outer-inner diameter ratio of 1:2 had the best <em>SEA</em> effect. In conclusion, this work provides new ideas for the design of bionic nested lattice structures.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 11-21"},"PeriodicalIF":6.8,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-scale oil well detection in remote sensing images based on MSA-Net: Background separation and dynamic optimization strategy","authors":"Zixiang Zhao ,&nbsp;Jiahui Li ,&nbsp;Xianye Bu ,&nbsp;Jinyu Wang ,&nbsp;Yan Xu","doi":"10.1016/j.aej.2025.08.043","DOIUrl":"10.1016/j.aej.2025.08.043","url":null,"abstract":"<div><div>Oil well detection is vital in remote sensing resource monitoring, significantly improving oilfield resource management and environmental protection. However, oil well targets pose challenges due to their small size, complex backgrounds, and diverse viewpoints. This paper proposes an innovative oil well detection framework to enhance detection accuracy and robustness. The framework combines multi-scale feature extraction, background separation, and enhancement techniques. First, the background separation module distinguishes oil well targets from the background, while the Generative Adversarial Network (GAN) enhances target saliency, reducing background interference. Then, a Feature Pyramid Network (FPN) is used for multi-scale feature extraction to handle various oil well target sizes and shapes, combined with an attention mechanism to optimize feature fusion for improved detection of small and partially occluded targets. Finally, an adaptive detection module adjusts the strategy based on target features, using bounding box regression and Non-Maximum Suppression (NMS) to refine results and ensure precise localization. Experimental results show significant improvements in performance, effectively addressing different target scales and occlusion issues, providing reliable support for oilfield management.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 22-34"},"PeriodicalIF":6.8,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}