Cleaner Engineering and Technology最新文献

{"title":"Applied machine learning multi-model benchmarking to plastic waste pyrolysis for optimizing crude oil yield production","authors":"Jose Romero Castro,&nbsp;Guinel Zapata Alfaro,&nbsp;Edilberto Avalos-Ortecho,&nbsp;Silvia Ponce Alvarez","doi":"10.1016/j.clet.2026.101198","DOIUrl":"10.1016/j.clet.2026.101198","url":null,"abstract":"<div><div>Optimizing crude fuel yield in catalytic pyrolysis of non-recyclable plastic waste remains a major challenge due to high-dimensional process variables and costly experiments. Machine Learning (ML) promises a data-driven solution, but published studies often report inflated performance from data leakage or improper Machine Learning applications. This study implements a leakage-free ML pipeline via a seven-stage Kanban workflow process applied to 754 pyrolysis experiments. 18 supervised ML algorithms, spanning neural networks, tree-based boosters, and ensemble methods, were evaluated. Tailored preprocessing imputation, dimensionality evaluation via PCA/KPCA, and synthetic augmentation were confined to training folds before stratified splitting. Model performance was assessed using MAE, MSE, RMSE, R², residuals, distribution analyses, and Q–Q plots under five-fold cross-validation. EvoTree Regressor was implemented in Julia for computational efficiency, while all other stages remained in Python. Also, real experimental reactor conditions were optimized via Particle Swarm Optimization (PSO), benchmarked against Random Search, yielding a 56.95 % liquid fraction (baseline 20 %). Results of crude oil show a calorific value of 17.94 kJ/g and density of 0.768 g/cm³ in 2 real experiment trials. FTIR analysis confirmed structural differences under optimized conditions. All code and data are openly available, establishing a reproducible, leakage-free framework to accelerate sustainable waste-to-fuel research.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101198"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612614","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":"Activated carbon–embedded free-standing glucomannan membrane for efficient dye removal","authors":"Masahide Hagiri ,&nbsp;Momoki Kanari ,&nbsp;Misaki Morota ,&nbsp;Keita Kashima","doi":"10.1016/j.clet.2026.101165","DOIUrl":"10.1016/j.clet.2026.101165","url":null,"abstract":"<div><div>A free-standing composite membrane was successfully fabricated by embedding activated carbon (AC) into a konjac glucomannan (KGM) matrix, and its performance in removing methylene blue (MB) from aqueous solution was evaluated. The resulting KGM and AC membrane exhibited high mechanical stability and uniform AC dispersion, which was achieved by incorporating polyethylene glycol as a dispersion aid. Adsorption experiments revealed that the membrane retained nearly the full adsorption capacity of raw powdered AC. For membranes with a mass fraction of AC (<em>MF</em>_AC) of 0.83, the capacity reached up to 280 mg g⁻¹, compared to 330 mg g⁻¹ for raw AC with <em>MF</em>_AC equal to 1.0. Although the adsorption rate decreased due to diffusion resistance within the membrane matrix, the equilibrium adsorption capacity remained comparable to that of the raw AC, indicating that the internal adsorption sites were fully accessible. The adsorption behavior followed the Langmuir isotherm, indicating monolayer adsorption, and the maximum capacity increased in proportion to <em>MF</em>_AC. Permeation experiments demonstrated that the membranes maintained a stable pure water flux under moderate pressure up to 0.30 MPa, with an estimated pore radius in the range of 10 to 50 nm. Under continuous flow conditions, the membranes achieved high rejection of MB greater than 99% until saturation, although some reduction in capacity was observed due to concentration polarization and internal transport limitations. These findings highlight the potential of KGM-based composite membranes as multifunctional adsorbents that are suitable for integrated adsorption and filtration systems in water purification.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101165"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191374","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 carbon emission monitoring method based on the average velocity across flue cross-sections","authors":"Yutong Jiang ,&nbsp;Chenghua Zhang ,&nbsp;Kaiwen Feng ,&nbsp;Zhihui Zheng ,&nbsp;Jing Yan ,&nbsp;Hairong Wang ,&nbsp;Lei Lan ,&nbsp;Hailiang Lu","doi":"10.1016/j.clet.2026.101155","DOIUrl":"10.1016/j.clet.2026.101155","url":null,"abstract":"<div><div>Accurate carbon accounting is essential for equitable global carbon trading, particularly in energy-intensive industries. Existing online monitoring systems enable real-time tracking of flue gas parameters but are often hindered by high costs and low accuracy. To address these challenges, this study proposes a carbon emission monitoring method based on the average flow velocity across the flue cross-section. Simulation results indicate that positioning sensors within the central 0.375D to 0.625D region (where D is the flue diameter) minimizes radial velocity deviations and improves measurement uniformity. A customized laboratory platform validated the proposed method, achieving a 5 % average error between measured and actual emissions. Field verification in a cement plant further demonstrated a relative error of 3.58 % compared with the traditional equal-area method. This method significantly reduces the number of required flow sensors while maintaining comparable accuracy, offering a cost-effective and reliable solution for industrial carbon emission monitoring.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101155"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090680","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":"Identifying and analyzing obstacles to ESG-driven sustainable transition in third-party logistics: A WINGS–ISM approach under interval-valued spherical fuzzy modeling","authors":"Detcharat Sumrit,&nbsp;Rodsak Kongsakul","doi":"10.1016/j.clet.2026.101157","DOIUrl":"10.1016/j.clet.2026.101157","url":null,"abstract":"<div><div>This study investigates the hierarchical structure and causal relationships among obstacles hindering the ESG driven sustainable transition of small and medium sized third-party logistics firms. Drawing on the resource-based view (RBV) and institutional (INT) theory, eleven obstacles are identified and validated, comprising eight endogenous and three exogenous factors. To address ambiguity, hesitation, and partial knowledge in expert judgments, the study adopts interval valued spherical fuzzy sets, which allow the simultaneous representation of membership, non-membership, and hesitancy degrees within bounded intervals. Compared with conventional Type 1 and Type 2 fuzzy sets, this approach provides greater expressive flexibility without imposing excessive computational or interpretability burdens in small expert panel studies. Using the Weighted Influence Nonlinear Gauge System (WINGS), six endogenous obstacles are revealed as dominant driving barriers, indicating that limitations in financial capacity, technological and digital infrastructure, process standardization, and sustainability capabilities primarily constrain ESG implementation, consistent with RBV logic emphasizing firm specific resources. In contrast, exogenous obstacles related to organizational culture, strategic alignment, regulatory coherence, governmental incentives, and stakeholder collaboration function mainly as dependent effect factors shaped by institutional conditions. Using Interpretive Structural Modeling (ISM) further identifies a five-level hierarchy, with obsolete technological infrastructure emerging as the root barrier. The study provides actionable insights for managers and policymakers seeking to design capability-oriented interventions and supportive institutional mechanisms to accelerate ESG transitions in SME logistics and other service intensive sectors.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101157"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191375","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":"Systematic digital framework for optimizing changeover cleaning in pharmaceutical industries","authors":"Megha Das,&nbsp;Gintaras V. Reklaitis,&nbsp;Zoltan K. Nagy","doi":"10.1016/j.clet.2026.101164","DOIUrl":"10.1016/j.clet.2026.101164","url":null,"abstract":"<div><div>A generalized and systematic framework for optimizing the changeover cleaning process in pharmaceutical manufacturing has been developed, with its application demonstrated in various scenarios to facilitate better decision-making regarding cleaning. This framework enhances cleaning decision-making by incorporating detailed modeling of various cleaning mechanisms tailored to common vessel configurations and cleaning modes prevalent in the industry. By extending the approach to entire process flowsheets comprising multiple unit operations, the framework proves effective in quantifying and demonstrating rational utilization of washing solvents and better non-productive downtime management associated with cleaning activities. The comprehensive analysis yields insights for the identification of optimal cleaning conditions that achieve regulatory cleanliness standards while minimizing operational cleaning costs by approximately up to 91% and environmental footprint quantified in terms of reduction in washing solvent consumption by approximately up to 87% when cleaned in the hybrid mode compared to cleaning all the unit operations in the same mode (i.e. either batch or continuous mode of cleaning). Overall, the proposed integrative methodology supports informed decision-making that advances greener, cost-effective, and operationally efficient cleaning strategies at the flowsheet level.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101164"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191486","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":"From theory to practice: a methodological roadmap for mapping, assessing, and implementing industrial symbiosis","authors":"Pawel Krzeminski ,&nbsp;Aleksandar Anastasovski ,&nbsp;Aleksandar Erceg ,&nbsp;Biljana Činčurak Erceg ,&nbsp;Carlos G. Dosoretz ,&nbsp;Massimo Borg ,&nbsp;Paul Refalo ,&nbsp;Radu Godina ,&nbsp;Angela Neves ,&nbsp;Vaida Jonaitienė ,&nbsp;Cansu Özcan Kılcan ,&nbsp;Alan H. Tkaczyk ,&nbsp;Aida Szilagyi ,&nbsp;Vasiliki Skoulou ,&nbsp;Yvonne Ryan ,&nbsp;Almudena Muñoz Puche","doi":"10.1016/j.clet.2026.101159","DOIUrl":"10.1016/j.clet.2026.101159","url":null,"abstract":"<div><div>Industrial symbiosis (IS) is a collaborative approach where industries share and reallocate resources, such as materials, energy, water, and by-products, create mutual benefits and contribute to a circular economy. This concept is limited due to the complexity of implementation and challenges with understanding the roadmap for their establishment. This study aims to bridge the gap between theory and practice by developing a comprehensive, methodologically grounded roadmap for implementing industrial symbiosis. The research combines a review of existing literature with the analysis of real-world case studies to identify and systematize the essential phases, tools, and success factors involved in the industrial symbiosis implementation process.</div><div>A detailed roadmap comprised key phases: mapping the current situation, identifying potential synergies, assessing feasibility, selecting the most appropriate opportunities, and implementing initiatives. The paper analyzes the relevant methods, tools and criteria for each phase. Particular attention is paid to key success factors, including resource and technology compatibility, geographical aspects, environmental impact, economic viability, and regulatory compliance. The importance of collaboration between different stakeholders and the role of intermediaries in the industrial symbiosis implementation process are highlighted. Based on the realized industrial symbiosis case studies, a few recommendations are given to support adopting industrial symbiosis strategies. The proposed roadmap emphasizes the importance of detailed resource flow mapping, multi-criteria assessment, and stakeholder collaboration with key success factors laying in evaluating technical, economic, environmental, and regulatory dimensions using appropriate tools.</div><div>Based on the research findings, the proposed roadmap consolidates fragmented approaches, supports strategic planning and provides practical guidance for companies and practitioners looking to integrate industrial symbiosis into their business. It contributes to a better understanding of the complexity of industrial symbiosis implementation and provides a framework for the wider adoption of these practices in the industry. This research contributes to the operationalization of industrial symbiosis by offering a replicable and adaptable roadmap. Further research should explore digital tools for synergy identification and assess policy mechanisms that can incentivize industrial symbiosis implementation at regional and national levels.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101159"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191489","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":"Review of industrial bioethanol production with a focus on volatile fermentation byproducts","authors":"Mahyar Mahdavi ,&nbsp;Aida Rashidi ,&nbsp;Bruce Dvorak ,&nbsp;Ashraf Aly Hassan","doi":"10.1016/j.clet.2026.101200","DOIUrl":"10.1016/j.clet.2026.101200","url":null,"abstract":"<div><div>The recent surge in biofuel production, particularly bioethanol production, marks a major stride toward renewable and sustainable fuel solutions. Bioethanol, derived from biomass, is mainly produced from starch- or sugar-rich crops, such as corn, wheat, and sugarcane, particularly in the United States and Brazil. However, the industrial production of bioethanol poses environmental challenges, notably the emission of volatile organic compounds (VOCs) from manufacturing facilities. This review explores VOC emissions associated with fermentation for ethanol production, with the aim of elucidating the formation mechanisms, prevention, monitoring, and treatment of volatile fermentation byproducts. Regulatory mandates require ethanol plants to mitigate the annual mass of hazardous air pollutant (HAP) emissions, which are traditionally managed using carbon dioxide scrubbers and regenerative thermal oxidizers. However, these conventional techniques require substantial amounts of water and natural gas. This review analyzes conventional and novel VOC removal methods in ethanol plants, offering comprehensive insights into this process. Additionally, the paper evaluates various Nebraska ethanol plants, comparing VOC and HAP emissions between large and small facilities, both with and without continuous emissions monitoring systems (CEMS). Results indicate smaller facilities employing CEMS are able to operate their air emissions systems more efficiently.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101200"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612628","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":"Metaheuristic-optimized machine learning models for predicting compressive strength and assessing sustainability of waste glass powder additive mortars","authors":"Izzeddin Donmez ,&nbsp;Kadir Gucluer","doi":"10.1016/j.clet.2026.101156","DOIUrl":"10.1016/j.clet.2026.101156","url":null,"abstract":"<div><div>The importance of waste management, waste recycling and ecological efficiency is felt more deeply every day. In this process where technological advances are developing rapidly, good studies can be carried out with the perspective of multidisciplinary approaches. For this purpose, in this study, it is aimed to evaluate and develop machine learning models optimized with meta-heuristic algorithms for the prediction of compressive strengths of mortars containing waste glass powder (WGP) with high accuracy in terms of sustainability. In this direction, Light Gradient Boosting Machine (LightGBM), Categorical Boosting (CB), Extremely Randomized Trees (ERT) and Random Forest (RF) algorithms were applied using a data set of 281 test result data compiled from 17 different scientific studies; the hyperparameters of these models were optimized with Particle Swarm Optimization (PSO) and Dwarf Mongoose Optimization (DMO) methods. At the same time, the most decisive variables within the mixture parameters were determined according to the SHAP-based variable importance analysis method. The experimental validation study, conducted to assess the real-world applicability and generalization capability of the optimized PSO-RF model, yielded an R² value of 0.841 based on comparisons performed on 60 test samples. In addition, the model was supported with sustainability analyses in terms of embodied energy (MJ/kg) and carbon emission (kg CO₂/kg); the ecological efficiency potential of waste glass powder usage was revealed. According to the obtained data, it was determined that the developed model has high prediction not only in theoretical data sets but also in the application field.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101156"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191373","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":"Highly efficient photocatalytic conversion of CO2 to hydrocarbons using visible-active co-doped TiO2/ PDMS nanocomposite","authors":"Majed Bahadorian ,&nbsp;Farzaneh Arabpour Roghabadi ,&nbsp;Vahid Ahmadi ,&nbsp;Afsanehsadat Larimi","doi":"10.1016/j.clet.2026.101147","DOIUrl":"10.1016/j.clet.2026.101147","url":null,"abstract":"<div><div>Considering the rising emission of the carbon dioxide (CO₂) and its detrimental effects on the environment, conversion of CO₂ into value-added products has emerged as a critical area of research. In particular, the photocatalytic reduction of CO₂ into fuels using solar energy has recently attracted significant attention. In this study, a nanocomposite of co-doped titanium dioxide (TiO₂) nanoparticles with polydimethylsiloxane (PDMS) is utilized for photocatalytic reduction of CO₂. Photo, chemical, and thermal-stable PDMS serves as a transparent flexible binder for photocatalyst nanoparticles, facilitating their usage and recycling. To make TiO₂ photocatalysts visible-active, reduce the charge recombination rate, and improve the charge transport and lifetime, they are co-doped using nonmetal nitrogen (N) and metal silver (Ag) with different concentrations. Following the optical, morphological, and structural analysis of the photocatalysts, their photocatalytic performance is evaluated in a fixed gas bed photoreactor. The TiO₂ photocatalyst shows the lowest yield for methane (3.2 μmol/g catalyst) and ethane (0.42 μmol/g catalyst). While, the yield for methane and ethane using Ag-N-TiO₂ photocatalyst reaches 34.42 and 1.01 μmol/g catalyst, respectively. Remarkably, when the PDMS-Ag-N-TiO₂ nanocomposite is employed, the highest methane and ethane yield of 122.21 and 10.22 μmol/g catalyst are achieved, respectively. Thus, in the presence of PDMS polymer, instantaneous quadrupolar interactions occur between its siloxane groups and carbon dioxide molecules. This promotes the adsorption of greater amounts of CO₂, making it more available for the photocatalytic reduction reaction and thereby enhancing hydrocarbon production.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101147"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191372","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":"Sustainably developing lithium resources from low-temperature sedimentary-basin brines","authors":"Xiaolong Peng,&nbsp;Chunqing Jiang,&nbsp;Wanju Yuan,&nbsp;Zhuoheng Chen","doi":"10.1016/j.clet.2026.101189","DOIUrl":"10.1016/j.clet.2026.101189","url":null,"abstract":"<div><div>Global electrification is accelerating research and development of using direct lithium extraction (DLE) technologies to unlock sedimentary-basin (SB) lithium (Li) brine resources. However, the techno-economic and environmental viability of these moderate-to-low grade ([Li] &lt;150 mg/L) and low-temperature (T_FM &lt;150 °C) brines remains poorly quantified. Here, we develop an integrated techno-economic–environmental framework that combines Monte Carlo simulations with coupled wellbore heat-loss, emission, and economic models to assess SB Li-brine development. We quantify the trade-offs between economic viability (in terms of Return on Sales) and environmental sustainability (in terms of carbon intensity, CI) for standalone DLE and three integrated pathways: geothermal heat recovery (GHR), geothermal power generation (GPG), and CO₂ capture (CC). Using Alberta's Devonian brines as a case study, we find that although most standalone DLE scenarios are economically viable, only 37.4% can achieve CI below the representative hard rock benchmark (∼15 kg CO_2e/kg LCE). GHR integration appears to be the most effective sustainable strategy as it can enable net-negative emissions and deliver 0.85-10.90 PJ/year of surplus heat. Implementation, however, still depends on local infrastructure and energy market conditions. Finally, we establish a game-theory-informed strategy matrix in [Li]-T_FM space to guide resource prioritization and sustainable strategy selection. This framework provides a transferable basis for optimizing sustainable lithium recovery from similar low-temperature SB brines worldwide.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101189"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612627","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}