Green Technologies and Sustainability最新文献

{"title":"Sustainable use of red mud in concrete: Assessing mechanical strength, durability, and performance through machine learning models","authors":"Jirapon Sunkpho ,&nbsp;Pradeep Thangavel ,&nbsp;Divesh Ranjan Kumar ,&nbsp;Warit Wipulanusat ,&nbsp;Jeung-Hwan Doh","doi":"10.1016/j.grets.2025.100283","DOIUrl":"10.1016/j.grets.2025.100283","url":null,"abstract":"<div><div>Red mud that is produced as a residue of alumina from bauxite ore through the Bayer process is undesirable or has potential environmental problems due to its large volume and high pH. Red mud was incorporated into the concrete mixtures at 0%, 5%, 10%, 15%, and 20% to determine the amount that enhances the strength and durability of the concrete. Furthermore, four machine learning models, including MARS, MPMR, GMDH, and ENN, were used in the present work to assess the compressive strength of red mud concrete and compare their efficacies. The replacement of cement with red mud in the range of 10% to 15% has beneficial effects on the acid, sulfate, and chloride resistance, as well as on the compressive and flexural strength, of concrete. Replacing 10% increased the compressive strength, and replacing 15% increased the flexural strength and durability. Replacement above 15% resulted in a decrease in the durability and strength of the concrete, which suggested the necessity of careful optimization. Among all the formulated models, the MARS model is the best predictor of compressive strength prediction on the basis of performance indicators, Taylor diagrams and comprehensive measurement analysis. Finally, the research validates that using red mud in concrete can be a sustainable solution that will lead to a green construction approach with long-standing impacts on the construction industry.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100283"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651991","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":"The role of fin–PCM integration in enhancing photovoltaic performance","authors":"Wibawa Endra Juwana ,&nbsp;Rendy Adhi Racmanto ,&nbsp;Ubaidillah ,&nbsp;Yuki Trisnoaji ,&nbsp;Singgih Dwi Prasetyo ,&nbsp;Zainal Arifin","doi":"10.1016/j.grets.2025.100306","DOIUrl":"10.1016/j.grets.2025.100306","url":null,"abstract":"<div><div>The efficiency and longevity of photovoltaic (PV) systems are fundamentally constrained by excessive operating temperatures, which reduce electrical output and accelerate material degradation. To address this issue, this study systematically reviews the integration of fin–Phase Change Material (fin–PCM) as a passive cooling strategy that enhances thermal and electrical performance. The review was conducted according to the PRISMA 2020 framework, covering 42 eligible studies published between 2020 and 2025, selected through a rigorous inclusion–exclusion process across four major databases (Scopus, Web of Science, ScienceDirect, and IEEE Xplore). Each study was evaluated based on technical, economic, and environmental performance indicators to provide an integrated understanding of the technology’s potential and limitations.</div><div>The findings indicate that fin–PCM configurations can increase thermal efficiency by up to 18.7% and reduce PV module peak temperatures by as much as 15 °C compared to conventional systems. These improvements result in an average electrical efficiency gain of 2.8%, with the best performance observed in porous and fractal fin geometries. However, a clear trade-off exists between technical enhancement and implementation complexity, as simpler straight-fin designs are more commercially ready (TRL 8). In contrast, advanced fin–PCM systems remain at early development levels (TRL 4). Economic analysis reveals that current configurations require an additional investment of approximately USD 350/kW, leading to a 16–17-year payback period and negative Net Present Value (NPV) under baseline conditions. Nevertheless, sensitivity-based optimization suggests that lowering costs below USD 250/kW and improving thermal efficiency beyond 22% can achieve an Internal Rate of Return (IRR) of around 28% within 15 years, making the technology economically feasible.</div><div>In conclusion, the integration of fin–PCM presents a promising pathway for improving PV system stability, efficiency, and sustainability. The study recommends phased commercialization beginning with industrial and commercial applications where high-value heat demand aligns with fin–PCM advantages. Future research should focus on large-scale field validation, cost-reduction strategies, and life cycle assessment to accelerate the transition of fin–PCM from laboratory innovation to market-ready renewable energy solutions.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100306"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651993","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":"Green computing for sustainability","authors":"Jumana Abdullah Kareem,&nbsp;Turkan Ahmed Khaleel","doi":"10.1016/j.grets.2025.100329","DOIUrl":"10.1016/j.grets.2025.100329","url":null,"abstract":"<div><div>Wireless network expansion needs intelligent solutions that combine energy-conscious operations with the maintenance of performance levels. This study presents an eco-friendly wireless ad hoc network framework that combines scheduled node deployment with adjustable packet time period control techniques, thus supporting renewable power sources. The model implementation in MATLAB enabled simulation testing, demonstrating performance evaluation against traditional networking protocols through key performance indicators. The experimental results show that energy consumption decreases substantially as node power consumption decreases from 23.43 Joules to 12.77 Joules in the case of 50 nodes, 93.38 Joules to 44.69 Joules for 200 nodes, and 234.08 Joules to 112 Joules for 500 nodes. The measured network performance improved slightly while the system maintained its initial output. Throughput evaluation revealed values between 4.008 Mbps and 4.084 Mbps, and latency stayed within 0.2467 ms to 0.2499 ms and achieved a packet delivery success rate of up to 90.15%. The proposed green model offers a sustainable and energy-efficient solution for wireless communications, ensuring that operation and service quality are maintained.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100329"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797959","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":"Artificial intelligence-based ensemble models with GUI for predicting the compressive strength of waste glass concrete","authors":"Sushant Poudel ,&nbsp;Bibek Gautam ,&nbsp;Sudip Khatiwada ,&nbsp;Bipin Lamichhane ,&nbsp;Prabin Kharel ,&nbsp;Diwakar KC ,&nbsp;Yong Je Kim","doi":"10.1016/j.grets.2025.100307","DOIUrl":"10.1016/j.grets.2025.100307","url":null,"abstract":"<div><div>The sustainable utilization of post-consumer waste glass in concrete has emerged as a promising approach to reduce cement consumption, mitigate landfill disposal, and enhance material performance. However, most previous predictive studies have relied on limited datasets, excluded chemical composition effects, or used single machine-learning algorithms, leading to restricted generalization. This study evaluates and develops artificial intelligence-based ensemble learning models to predict the compressive strength of concrete incorporating waste glass powder (WGP) as a partial cement replacement. A dataset of 337 experimental results was compiled from the literature published between 2007 and 2024, including eleven key input variables such as WGP size and replacement level, water-to-cement ratio (W/C), aggregate properties, curing age, and chemical composition of WGP (SiO₂, CaO, Na<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>O). Five advanced ensemble algorithms — Gradient Boosting Regressor, Extreme Gradient Boosting Regressor, LightGBM Regressor, CatBoost Regressor, and Histogram-based Gradient Boosting regressor — were trained and optimized using Bayesian hyperparameter tuning and validated with 10-fold cross-validation. Performance was assessed using R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>, RMSE, MSE, MAE, and MAPE metrics. All models demonstrated excellent predictive ability (R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>\u0000 <span><math><mo>&gt;</mo></math></span> 0.94), with CatBoost achieving the highest testing accuracy (R<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span> = 0.96, RMSE = 2.34 MPa, MAE = 1.63 MPa). Feature importance and SHAP analysis revealed curing time and W/C as the most influential parameters, followed by aggregate content and WGP replacement level. Parametric studies confirmed the expected concrete behavior, with strength gains over curing time and reductions at high WGP replacement and W/C. A graphical user interface (GUI) was developed using the CatBoost model, enabling the practical prediction of compressive strength for various mix designs. The integration of chemical composition-based modeling, ensemble learning optimization, and GUI deployment establishes a practically oriented framework that advances sustainable concrete design and facilitates its broader adoption within the construction industry.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100307"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694332","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":"Carbon neutrality in high-altitude agricultural systems: Examples and insights from the Qinghai–Tibet Plateau","authors":"Zhihua Mu ,&nbsp;Shuya Yang ,&nbsp;Ke Deng ,&nbsp;Muhammad Zohaib Nawaz ,&nbsp;Mehvish Zahoor ,&nbsp;Jian Wang ,&nbsp;Long Zhao","doi":"10.1016/j.grets.2026.100350","DOIUrl":"10.1016/j.grets.2026.100350","url":null,"abstract":"<div><div>The Qinghai–Tibet Plateau, often referred to as the “Third Pole” and the “Asian Water Tower”, plays a pivotal role in global climate regulation due to its exceptional carbon sequestration capacity. Recent evidence indicates that terrestrial carbon sinks across the Plateau offset moat regional anthropocentric emissions (focused on CO₂, CH₄, <span><math><msub><mrow><mtext>N</mtext></mrow><mrow><mn>2</mn></mrow></msub></math></span>O from local energy, livestock, and natural ecosystems), supporting the region’s progress toward a net-zero balance of direct GHG emissions—one of the earliest such trends observed in China. This paper explores the transition of the Plateau’s agricultural sector toward low-carbon development, emphasizing integrated approaches such as renewable energy adoption, circular agricultural models, grassland restoration, and emerging carbon market mechanisms. These strategies collectively enhance ecological resilience while reducing greenhouse gas emissions. Nonetheless, the transition faces persistent challenges, including infrastructural deficiencies, technical limitations, and socioeconomic disparities that constrain large-scale implementation. Addressing these barriers requires targeted policy support, sustained technological innovation, and strengthened cross-regional cooperation. The Plateau’s experience demonstrates the potential for aligning ecological conservation with sustainable agricultural development in fragile high-altitude ecosystems. Moreover, it provides a replicable model for other regions seeking to achieve carbon neutrality under similar environmental constraints. By linking local adaptation with broader global mitigation goals, the Qinghai–Tibet Plateau highlights the strategic importance of integrated low-carbon pathways in securing both ecological security and rural livelihoods.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100350"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188319","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":"Corrigendum to “Moisture-induced swelling in natural fiber-reinforced composites: A critical review of chemical treatments, hybrid strategies, and environmental durability” [Green Technol. Sustain. 4 (2026) 100336]","authors":"Riduwan Prasetya ,&nbsp;Femiana Gapsari ,&nbsp;Andoko Andoko ,&nbsp;Khairul Anam ,&nbsp;Rudianto Raharjo ,&nbsp;Sanjay Mavinkere Rangappa ,&nbsp;Suchart Siengchin","doi":"10.1016/j.grets.2026.100349","DOIUrl":"10.1016/j.grets.2026.100349","url":null,"abstract":"","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100349"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188323","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":"Interactive co-pyrolysis of leucine amino acid and plastic wastes using TGA-IR-MS connection","authors":"Ahmad Yaghi ,&nbsp;Labeeb Ali ,&nbsp;Mohammednoor Altarawneh","doi":"10.1016/j.grets.2025.100328","DOIUrl":"10.1016/j.grets.2025.100328","url":null,"abstract":"<div><div>Waste materials from agricultural and food packaging usage pose significant health and environmental challenges, where the main source of waste originates from plastics and protein-based amino acids, and their thermal degradation is often investigated separately for the production of waste-to-energy. Therefore, this research investigates the products of a specific amino acid called leucine and its co-pyrolysis with different plastic waste, like polypropylene (PP), polyethylene (PE), and polyethylene terephthalate (PET), to recognize their interactions with the nitrogen compounds. The system used for this reaction is an integrated TGA-IR-MS that can effectively mimic the thermal degradation of these blends and their gas analysis by evaluating the pyrolysis behaviour and nitrogen emissions. Pure leucine degradation proved the production of 87% nitrogen-rich compounds like amines and nitriles with a high endothermic demand of 1009 J/g, while the PE and PP blends enhanced the degradation properties by reducing the enthalpy by 60% and suppressing the nitrogen production to 10% for PP and &lt;5% for PE blends, while promoting the formation of rich hydrocarbons like 2,4-dimethyl heptane with over 70% relative yield. Nonetheless, PET had a different interaction since it enhanced the reaction of leucine and increased the nitrogen production while providing high oxygen content, proven by the FTIR (C=O at 1750 cm ⁻¹) with 15% char content. These interactions were promoted via radical mechanisms. The reported results address multiple suitability challenges that are related to clean and affordable energy.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100328"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145750382","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":"Empirical analysis of circular economy–Industry 4.0 integration for enhancing sustainable performance: A multi-level framework across micro, meso, and macro","authors":"Than’a Alsaoudi ,&nbsp;Adolf Acquaye","doi":"10.1016/j.grets.2026.100356","DOIUrl":"10.1016/j.grets.2026.100356","url":null,"abstract":"<div><div>The integration of circular economy (CE) practices with Industry 4.0 (I4.0) technologies in industrial sectors remains limited, primarily due to a lack of practical knowledge about key drivers, barriers, and mitigation strategies. Despite their strong potential to enhance sustainable performance (SP), the adoption of CE–I4.0 faces several challenges across organizational levels. This study aims to empirically investigate the key drivers, barriers, and mitigation strategies for effective CE–I4.0 adoption, focusing on micro, meso, and macro-organizational contexts. Data were collected through an open-ended survey of 287 professionals, including sustainability leaders, managers, executives, and consultants, with 128 responses from micro level organizations, 87 from meso level organizations, and 71 from macro level organizations. The findings reveal level-specific drivers: “Technological innovation” at the micro level, “Regulatory pressure and sustainability standards” at the meso level, and “Regulatory and policy support” at the macro level. Across all levels, financial constraints emerged as the most critical barrier: “High initial investment costs” at the micro level, “High capital investment requirements” at the meso level, and “High upfront and ongoing costs” at the macro level. Mitigation strategies varied accordingly, including financial, skill, and change management at the micro level; education, collaboration, and technology adoption at the meso level; and awareness, stakeholder engagement, and infrastructure development at the macro level. These results underscore the need to tailor interventions to organizational scale while coordinating system-wide actions for enhanced sustainability. The study introduces a CE–I4.0 integration framework that consolidates these insights into an evidence-based roadmap linking drivers, barriers, and strategies across levels, providing actionable guidance for managers and policymakers. By offering a multi-level empirical analysis of CE–I4.0 integration, the study advances theory and practice, supporting coordinated adoption that enhances efficiency, sustainability, and organizational resilience.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100356"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188322","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 design method for agricultural product logistics cold chain distribution routes based on a genetic algorithm","authors":"Hong Yuan,&nbsp;Xuefen Yang","doi":"10.1016/j.grets.2026.100335","DOIUrl":"10.1016/j.grets.2026.100335","url":null,"abstract":"<div><div>In this study, a new methodology is developed to optimize cold chain distribution routes of agricultural products with a view to reducing the costs of distribution. It develops a mathematical model that considers multiple costs, including fixed costs, transportation costs, cooling costs, cargo loss, and time penalties, all of which have been addressed in separate studies in previous research works. By incorporating a genetic algorithm (GA) into the mathematical model of this study, it is possible to optimize the distribution routes of agricultural products for Company Y across 16 cities, while considering the Vehicle Routing Problem with Time Window constraints. This study is unique in its methodology as it considers a diverse range of costs in an integrated manner that makes it realistic and practical at the same time. This study is also realistic in its objectives as it aims to develop a model that minimizes the total costs of distribution by 25.87% while reducing the costs of time penalties by 41.98%. Moreover, analysis of vehicle speed also indicates that an optimized truck speed of 60 km/h is helpful in reducing costs of distribution while improving truck performance in terms of 52.58%–94.72% increased loadability as well as 352.6 km lower mileage.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100335"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188324","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":"Integration of lignocellulosic waste (Sonneratia-ovata) derived silver nanoparticle with naturally available halloysite nanotubes for efficient organic dye pollutants removal","authors":"Deepak Verma ,&nbsp;Senthilkumar Nangan ,&nbsp;Kalidasan Kaliyamoorthy ,&nbsp;Hiroshi Uyama ,&nbsp;Manunya Okhawilai","doi":"10.1016/j.grets.2025.100282","DOIUrl":"10.1016/j.grets.2025.100282","url":null,"abstract":"<div><div>The drinkable water scarcity has been increased worldwide due to the mixing of numerous hazardous organic and inorganic pollutants in water bodies, urging to find sustainable water remediation techniques. In this work, the naturally available HNT was modified with Ag nanoparticles through lignocellulosic waste material, i.e., <em>Sonneratia Ovata</em> leaf extract. A <em>Sonneratia Ovata</em> leaf derived Ag nanoparticle loaded halloysite nanotubes catalyst have developed with varying Ag nanoparticles loading over HNT surface, i.e., 0.25:1, 0.5:1, 0.75:1. Various characterization techniques were performed to confirm the formation of the Ag nanoparticles over HNTs surface. Then the prepared Ag loaded HNTs (Ag@HNT) were employed as photocatalysts for the removal of Methylene blue dye. It has been observed that, as compared to bare HNT, Ag@HNT based catalyst with ratio 0.5:1 exhibited efficient dye degradation. Around 95% of dye degraded within 30 min as confirmed by UV-vis spectrometer. Furthermore, to explore the kinetics and adsorption isotherm of the dye removal reaction under the presence of prepared catalysts, the models including pseudo first and pseudo second order, Elovich model, intraparticle diffusion, Langmuir model, Freundlich model, and Temkin model were detailed. The novelty of the present investigation lies in the development of a green synthesis method for silver nanoparticles using mangrove leaf (<em>Sonneratia-Ovata</em>) extract without any toxic reducing agent. Also, the naturally available HNT used as a substrate to support the formation of catalytically active silver nanoparticles. The prepared material produces high catalytic activity than previously reported results.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100282"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651989","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}