Water Research X最新文献

{"title":"Overlooked role of long capping time and environmental factors in the plateau lake for impairing lanthanum-modified-bentonite's immobilization to phosphate","authors":"Jinhui Wang ,&nbsp;Lina Chi ,&nbsp;Shuai Liu ,&nbsp;Jiao Yin ,&nbsp;Youlin Zhang ,&nbsp;Jian Shen ,&nbsp;Xinze Wang","doi":"10.1016/j.wroa.2024.100272","DOIUrl":"10.1016/j.wroa.2024.100272","url":null,"abstract":"<div><div>Lanthanum-modified-bentonite(LMB) has been applied for eutrophication management as a phosphate(P)-binding agent in many lakes. However, re-eutrophication took place several years or decades later after the first practice of capping due to dynamic environmental factors in the plateau lake. Here, we investigated the effect of long-term capping and integrated environmental factors in the plateau lake including alkalinity, organic matter, disturbance and photodegradation to the LMB immobilization. Long-term LMB immobilization exhibited C accumulation(82.3%), La depletion(53.5%) and lager size effect in the sediment particle, indicating the breakage of La-O-P bonds and the formation of La-O-C bonds over immobilization time. Additionally, pH(8–10) in the plateau lake could enhance the P desorption and decrease P adsorption through electrostatic repulsion enhancement with the zeta potential reduction(7.2 mV). Further disturbance experiment indicated a significant releasing trend of active P and DGT-labile P from the solid phase, pore water to the overlying water after disturbances due to resuspended releasing, particle size and amorphous Fe, Mn and Al's redistribution. Moreover, ³¹P NMR and EPR results indicated photodegradation after disturbance converted diester phosphate into orthophosphate with long-term LMB immobilization via the oxidation of ·OH in the sediment of the plateau lake. Therefore, management issues for Xingyun Lake may apply to other plateau lakes with low external P input, intermediate depth and intense disturbance.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100272"},"PeriodicalIF":7.2,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-sewer iron dosing enhances bioenergy recovery in downstream sewage sludge anaerobic digestion: The impact of iron salt types and thermal hydrolysis pretreatment","authors":"Jingya Xu ,&nbsp;Yizhen Wang ,&nbsp;Yanzhao Wang ,&nbsp;Lai Peng ,&nbsp;Yifeng Xu ,&nbsp;Hailong Yin ,&nbsp;Bin Dong ,&nbsp;Xiaohu Dai ,&nbsp;Jing Sun","doi":"10.1016/j.wroa.2024.100273","DOIUrl":"10.1016/j.wroa.2024.100273","url":null,"abstract":"<div><div>Dosing iron salts is a widely adopted strategy for sewer odor and corrosion management, and it can affect bioenergy recovery during anaerobic digestion (AD) of sludge in downstream wastewater treatment plants. However, the different impacts of in-sewer iron salt dosing on AD, depending on the types of iron and digestion conditions, remain unclear. Therefore, this study investigated the impact of in-sewer ferrous (Fe(II)) and ferrate (Fe(VI)) dosing on bioenergy recovery in both conventional AD and AD with thermal hydrolysis pretreatment (THP). The results showed that in-sewer Fe(VI) dosing notably enhanced methane production in AD more than in-sewer Fe(II) dosing, with cumulative methane yields of 197.1±1.9 mLCH₄∙gVSadded⁻¹ for Fe(VI) and 186.5±10.4 mLCH₄∙gVSadded⁻¹ for Fe(II), respectively. Microbial analyses and iron particle characterizations suggested that the superior promotion with Fe(VI) dosing may be attributed to the smaller particle sizes and higher iron oxide content of Fe(VI) resultant products. This led to a greater enhancement in direct interspecies electron transfer (DIET) between syntrophic bacteria and methanogens, as indicated by the upregulation of <em>Methanosaeta</em> and key functional genes involved in CO₂-utilizing methanogenesis. Additionally, in THP-AD, the methane production enhancement caused by in-sewer iron dosing (35.5 mLCH₄∙gVSadded⁻¹) exceeded that in conventional AD (26.9 mLCH₄∙gVSadded⁻¹), although organic degradation during THP was unaffected. As THP-AD gains popularity for improved bioenergy recovery from sludge, our findings suggest that in-sewer iron dosing supports this advancement. Furthermore, in-sewer Fe(VI) dosing appears more promising within integrated wastewater management strategies, facilitating energy- and carbon-neutralization of urban water systems.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100273"},"PeriodicalIF":7.2,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and sustainable removal of linear alkylbenzene sulfonate in a membrane biofilm: Oxygen supply dosage impacts mineralization pathway","authors":"Ting Wei,&nbsp;Ting Ran,&nbsp;Weikang Rong,&nbsp;Yun Zhou","doi":"10.1016/j.wroa.2024.100268","DOIUrl":"10.1016/j.wroa.2024.100268","url":null,"abstract":"<div><div>Linear alkylbenzene sulfonate (LAS) can be thoroughly mineralized within sufficient oxygen (O₂), but which is energy intensive and may causes serious foaming problem. Although cometabolism can achieve efficient LAS removal within a wide range of O₂ dosages, how O₂ dosage systematically affects LAS metabolic pathway is still unclear. Here, membrane aerated biofilm reactor (MABR) enabled accurate O₂ delivery and bulk dissolved oxygen (DO) control. MABR achieved efficient removal of LAS (&gt;96.4 %), nitrate (&gt;97.8 %) and total nitrogen (&gt;96.2 %) at the three target DO conditions. At high DO condition (0.6 mg/L), LAS was efficiently removed by aerobic mineralization (predominant) coupled with aerobic denitrification biodegradation with the related functional enzymes. <em>Pseudomonas, Flavobacterium, Hydrogenophaga</em>, and <em>Pseudoxanthomonas</em> were dominant genus contributing to four possible LAS aerobic metabolic pathways. As O₂ dosage reduced to only 29.7 % of the demand for LAS mineralization, O₂ facilitated LAS activation, benzene-ring cleavage and a portion of respiration. NO₃^--N respiration-induced anaerobic denitrification also contributed to ring-opening and organics mineralization. <em>Desulfomicrobium</em> and <em>Desulfonema</em> related two possible anaerobic metabolic pathways also contributed to LAS removal. The findings provide a promising strategy for achieving low-cost high LAS-containing greywater treatment.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100268"},"PeriodicalIF":7.2,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water demand forecasting in multiple district metered areas based on a multi-scale correction module neural network architecture","authors":"Qidong Que ,&nbsp;Jinliang Gao ,&nbsp;Yizhou Qian","doi":"10.1016/j.wroa.2024.100269","DOIUrl":"10.1016/j.wroa.2024.100269","url":null,"abstract":"<div><div>Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture—the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms—for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy. This framework utilizes multivariate corrections to refine and enhance the output accuracy. The results reveal that, in comparison to traditional Gated Recurrent Unit or LSTM models, the proposed model with integrated correction modules, particularly those that leverage inter-DMA correlations, improves performance across all evaluation metrics by an average of 5 %-20 % per DMA. Additionally, it consistently delivers superior accuracy across three scenarios: single DMA forecasting, total water demand, and extreme conditions, while maintaining stable performance throughout. Furthermore, the interpretability analysis underscores the feasibility of this innovative structure and highlights the contribution of meteorological features to the predictive model in some DMA-level STWDF. The unified input-output framework elegantly simplifies the STWDF process across multiple DMAs, providing new insights and methodologies for future research in this domain.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100269"},"PeriodicalIF":7.2,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Near-Complete Phosphorus Recovery from Challenging Water Matrices Using Multiuse Ceramsite Made from Water Treatment Residual (WTR)","authors":"Jianfei Chen ,&nbsp;Jinkai Xue ,&nbsp;Jinyong Liu ,&nbsp;Seyed Hesam-Aldin Samaei ,&nbsp;Leslie J. Robbins","doi":"10.1016/j.wroa.2024.100267","DOIUrl":"10.1016/j.wroa.2024.100267","url":null,"abstract":"<div><div>Water treatment residual (WTR) is a burden for many water treatment plants due to the large volumes and associated management costs. In this study, we transform aluminum-salt WTR (Al-WTR) into ceramsite (ASC) to recover phosphate from challenging waters. ASC showed remarkably higher specific surface area (SSA, 70.53 m²/g) and phosphate adsorption capacity (calculated 47.2 mg P/g) compared to previously reported ceramsite materials (&lt; 40 m²/g SSA and &lt; 20 mg P/g). ASC recovered over 94.9% of phosphate across a wide pH range (3 – 11) and generally sustained &gt; 90% of its phosphate recovery at high concentrations of competing anions (i.e., Cl^-, F^-, SO₄^2-, or HCO₃^-) or humic acid (HA). We challenged the material with real municipal wastewater at 10°C and achieved simultaneous phosphate (&gt;97.1%) and COD removal (71.2%). Once saturated with phosphate, ASC can be repurposed for landscaping or soil amendment. The economic analysis indicates that ASC can be a competitive alternative to natural clay-based ceramsite, biochar, or other useful materials. Therefore, ASC is an eco-friendly, cost-effective adsorbent for phosphate recovery from complex waters, shedding light upon a circular economy in the water sector.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100267"},"PeriodicalIF":7.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling transient mixed flows in sewer systems with data fusion via physics-informed machine learning","authors":"Shixun Li ,&nbsp;Wenchong Tian ,&nbsp;Hexiang Yan ,&nbsp;Wei Zeng ,&nbsp;Tao Tao ,&nbsp;Kunlun Xin","doi":"10.1016/j.wroa.2024.100266","DOIUrl":"10.1016/j.wroa.2024.100266","url":null,"abstract":"<div><div>Transitions between free-surface and pressurized flows, known as transient mixed flows, have posed significant challenges in urban drainage systems (UDS), e.g., pipe bursts, road collapses, and geysers. However, traditional mechanistic modeling for mixed flows is challenged by the difficult integration of multi-source data, complex equation forms for the discovery of dynamic processes, and high computational demands. In response, we proposed a data-driven model, TMF-PINN, which utilizes a Physics-Informed Neural Network (PINN) to simulate and invert Transient Mixed Flow (TMF) in sewer networks. This model integrates experimental data, simulation results and Partial Differential Equations (PDEs) into its loss function, leveraging the extensive data available in smart urban water systems. A status factor (<em>α</em>) has been introduced to seamlessly link open channel and pressurized flow dynamics, facilitating rapid adjustments in wave speed. On this basis, Fourier feature extraction and quadratic neural networks have been employed to capture complex dynamic processes featuring high-frequency. Validation through three classical cases using the Storm Water Management Model (SWMM) and comparisons with finite volume Harten-Lax-van Leer (HLL) solver reveal that the proposed model circumvents the constraints of spatiotemporal resolution, yielding accurate flow field predictions.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100266"},"PeriodicalIF":7.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid and selective quantitative colourimetric analysis of nitrite in water using a S-Nitrosothiol based method","authors":"E. Latvyte ,&nbsp;A. Greenwood ,&nbsp;A. Bogush ,&nbsp;J.E. Graves","doi":"10.1016/j.wroa.2024.100265","DOIUrl":"10.1016/j.wroa.2024.100265","url":null,"abstract":"<div><div>This study introduces a novel S-nitrosothiol based method for the rapid and highly selective detection of nitrite in complex water matrices. Sodium 3-mercapto-1-propanesulfonate forms a distinctive pink S-nitrosothiol compound upon interaction with nitrite in acidic media, allowing both visual and quantitative detection. Various factors affecting the absorbance of the final product were investigated, including pH, reaction time, acid type, and sodium 3-mercapto-1-propanesulfonate concentration. UV–Vis spectrophotometric analysis demonstrated an excellent linear correlation (R² = 0.99) across a broad detection range (0.05 to 80 mmol <span>l</span>^-1), while showing no interference from common ions such as nitrate or dissolved organic matter, a limitation frequently observed in conventional UV-based nitrite detection methods. The assay was further adapted into a pellet form to simplify field use, operating effectively at room temperature with a low detection limit (1.4 ppm). The S-nitrosothiol based method represents a safer and more environmentally friendly option for nitrite detection and shows a promising potential as a valuable addition to both field and laboratory water testing kits for nitrite analysis.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100265"},"PeriodicalIF":7.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three-dimensional convolutional neural network for leak detection and localization in smart water distribution systems","authors":"Sanghoon Jun ,&nbsp;Donghwi Jung ,&nbsp;Kevin Lansey","doi":"10.1016/j.wroa.2024.100264","DOIUrl":"10.1016/j.wroa.2024.100264","url":null,"abstract":"<div><div>Smart meters such as advanced metering infrastructure (AMI) can significantly improve identifying realistic sized leaks in water distribution networks (WDNs). However, to date, detection/localization methods for AMI systems are extremely limited. In this study, to examine the benefits of using AMIs for leak detection within distribution network, a three-dimensional (3D) convolutional neural network (CNN) deep learning (DL) model is proposed that can account for temporally and spatially distributed information of pressures. The 3D CNN is tested for a real WDN in Austin using the realistic sized leaks (e.g., 3 L/s for 150-mm pipes) that are generated from hydraulic simulations. The model's performance is evaluated using detection probability, false alarm rate, and localization pipe distance metrics. In addition, the strength of using DL for leak identification is examined by comparing the CNN results with those from an optimization-based model. The 3D CNN performed better than the optimization model indicating that DL has advantages over conventional tools such as optimization methods. However, its adaptability may limit its use in some cases. Since DL can be significantly impacted by hydraulic simulation model, a way to handle modelling error must be determined. In addition, as network changes occur, retraining is required that may be time consuming and have difficulty with the number of failure conditions.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100264"},"PeriodicalIF":7.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coarse bubble mixing in anoxic zone greatly stimulates nitrous oxide emissions from biological nitrogen removal process","authors":"Haoran Duan ,&nbsp;Shane Watt ,&nbsp;Dirk Erler ,&nbsp;Huijuan Li ,&nbsp;Zhiyao Wang ,&nbsp;Min Zheng ,&nbsp;Shihu Hu ,&nbsp;Liu Ye ,&nbsp;Zhiguo Yuan","doi":"10.1016/j.wroa.2024.100263","DOIUrl":"10.1016/j.wroa.2024.100263","url":null,"abstract":"<div><div>The biological nitrogen removal process in wastewater treatment inevitably produces nitrous oxide (N₂O), a potent greenhouse gas. Coarse bubble mixing is widely employed in wastewater treatment processes to mix anoxic tanks; however, its impacts on N₂O emissions are rarely reported. This study investigates the effects of coarse bubble mixing on N₂O emissions in a pilot-scale mainstream nitrite shunt reactor over a 50-day steady-state period. Online and offline N₂O monitoring campaigns show that coarse bubble mixing in the anoxic zones significantly elevates N₂O emissions, yielding an extremely high emission factor of 15.5 ± 3.5 %. Intensive sampling and isotopic analyses suggest that the elevated emissions are primarily due to the inhibition of the N₂O denitrification process by oxygen in the anoxic phase introduced by coarse bubbling. Substituting coarse bubble mixing with submersible pump mixing resulted in a substantial reduction of N₂O emissions, decreasing the emission factor by an order of magnitude to 1.2 ± 0.8 %. The findings reveal that a previously overlooked factor, coarse bubble mixing, can significantly stimulate N₂O emissions. The use of coarse bubble mixing in anoxic tanks of biological nitrogen removal warrants caution.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100263"},"PeriodicalIF":7.2,"publicationDate":"2024-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of blue-green infrastructure on trace contaminants: A catchment-wide assessment","authors":"Marisa Poggioli ,&nbsp;Giovan Battista Cavadini ,&nbsp;Zhaozhi Zheng ,&nbsp;Mayra Rodriguez ,&nbsp;Lena Mutzner","doi":"10.1016/j.wroa.2024.100261","DOIUrl":"10.1016/j.wroa.2024.100261","url":null,"abstract":"<div><div>Blue-green infrastructure (BGI) reduce urban combined sewer overflows (CSOs) and stormwater outlets (SWOs). However, most conventional BGI are not designed to remove trace organic contaminants. Little is known about the potential of conventional BGI to improve surface water quality by reducing the discharge of trace organic contaminants. We derived wash-off loads for street runoff (6PPD-q, DPG, and HMMM), construction materials (diuron), and wastewater-derived contaminants (diclofenac) based on measurements in the combined sewer system. Subsequently, the performance of four BGI types (bioretention cells, green roofs, porous pavements, and urban wetlands) to reduce the discharge of trace organic contaminants via SWOs and CSOs was quantified with a hydrodynamic SWMM model. Moreover, the catchment-wide impact of SWOs and CSOs on surface water was assessed using risk quotients. We found that the annually discharged load can be considerably reduced by implementing BGI. Among the studied BGI types, bioretention cells are the most effective, with a load reduction of up to 80% to surface waters, mainly due to a larger suitable implementation area and a substantial stormwater infiltration. BGI implemented in the separate sewer system are more effective in reducing stormwater contaminant loads than BGI in the combined system. The assessment of the risk quotient in the surface water showed that the concentrations during SWO and CSO discharges exceed the acute environmental threshold in the surface water for 6PPD-q, DPG, diuron, and diclofenac during several events. The implementation of BGI reduced the hours of exceeded risk quotient in the surface water by 93% for bioretention cells. These findings underscore the need for a catchment-wide assessment of future BGI implementations to quantify, manage, and mitigate the impacts of urban pollution.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"25 ","pages":"Article 100261"},"PeriodicalIF":7.2,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}