Building and Environment最新文献

{"title":"Factors shaping fungal contamination emissions from cooling coils: An experimental study across hot-humid and hot-dry climates in Shanghai","authors":"Yuqian Gu ,&nbsp;Wei Yang ,&nbsp;Ke Zhong ,&nbsp;Zili Yang","doi":"10.1016/j.buildenv.2025.112820","DOIUrl":"10.1016/j.buildenv.2025.112820","url":null,"abstract":"<div><div>Cooling coils in air-conditioning systems can compromise indoor air quality by fostering fungal growth and dispersing spores, posing health risks to occupants. However, the climate and operational factors shaping coil-induced airborne fungal contamination remain unclear, impeding the development of effective mitigation strategies. This study developed a lab-scale system with three coil rows to examine fungal contamination dynamics during the transition from the hot-humid plum rain season to the hot-dry heat wave period in Shanghai. A 55-day experiment was conducted following a standard office-hour schedule (9:00 to 17:00), with daily fungal sampling from air, coil surfaces, and condensate. Results showed that coil-induced fungal contamination depends on climate, system's operation duration, and coil row position, with condensate often heavily polluted. Humid climates amplified fungal emissions, particularly upon morning coil activation. Fungal level in downstream air increased by 24.5% on hot-humid mornings but decreased by 36.3% on hot-dry mornings. Hot-humid conditions also enriched allergenic species, such as <em>Aspergillus</em> and <em>Malassezia</em>, in downstream air. Additionally, continuous coil operation heightened fungal exposure risks, emitting respirable fungal particles into downstream air at nearly triple the upstream levels after three consecutive hot-humid mornings. Rear-row coils were the dominant emission sources, as evidenced by a “J-shaped” fungal distribution on coil surfaces: front-row coils cleared fungal deposits via condensate drainage, while rear-row coils retained moisture, promoting fungal proliferation and spore dissemination. These findings underscore cooling coils as substantial indoor fungal sources in hot-humid climates upon activation, emphasizing the need for targeted rear-row coil maintenance to mitigate fungal emissions.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112820"},"PeriodicalIF":7.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty analysis of two-level heating demand in pastoral areas of eastern Qinghai-Tibet Plateau based on field investigation and numerical simulation","authors":"Jinwei Li ,&nbsp;Rongjiang Ma ,&nbsp;Mengsi Deng ,&nbsp;Xiaoling Cao ,&nbsp;Xianfeng Liu ,&nbsp;Pengxin Zhang ,&nbsp;Changyue Hu ,&nbsp;Xinke Luo ,&nbsp;Yuanwei Han ,&nbsp;Ke Zhang ,&nbsp;Yitong Luo ,&nbsp;Zongyan Li ,&nbsp;Qinghai Hu","doi":"10.1016/j.buildenv.2025.112818","DOIUrl":"10.1016/j.buildenv.2025.112818","url":null,"abstract":"<div><div>The Qinghai-Tibet Plateau is suitable for clean heating due to its abundant solar energy resources. However, the climate and living habits in this area are different from other areas of China. To study the impact of weather and residents' habits on heating load, residents' habits were obtained through field measurement and questionnaire survey, and eight typical buildings were summarized. The fifty years of reanalysis weather data are used to describe weather uncertainties. Finally, two levels of heating load uncertainty are studied. The first level is the heating load at the building level; the second level is the heating load at the village level considering the herding activities of residents. The results show that when the uncertainty of weather and behavior is considered, the peak heating load of the building in these areas will be 24.03 % to 106.78 % higher than the results under the design standard. When the uncertainty of the building occupancy rate caused by herding activities is considered, the peak heating load of the seven villages in these areas will be about 14.97 % to 45.23 % lower than the results of the design standard under the 95.0 % satisfaction rate. These results provide a reference for the future design of decentralized and centralized heating systems in the eastern Qinghai-Tibet Plateau area.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"276 ","pages":"Article 112818"},"PeriodicalIF":7.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic information gain-guided convergence for refining building design parameters: Enhancing effectiveness and interpretability in simulation-based optimization","authors":"Qianyun Zhou ,&nbsp;Fan Xue","doi":"10.1016/j.buildenv.2025.112788","DOIUrl":"10.1016/j.buildenv.2025.112788","url":null,"abstract":"<div><div>Simulation-based optimization (SBO) is widely applied to building designs by iteratively tuning design parameters towards sustainable goals. However, numerous design parameters in exploratory stages lead to design uncertainty and exponentially increase optimization search space’s dimensionality. The non-linear, non-derivative nature of objective functions determines SBO tasks a black box, which lacks interpretability for design decisions or optimization strategies. This study introduces an Automatic Information Gain-guided Convergence (AIGGC) method for refining critical design parameters in building performance SBO. The AIGGC method extends the generic SBO process with interpretable information gain analysis for each design parameter and component, to converge to the most promising domain sub-intervals prior to traditional SBOs. Experimental results evaluated the robustness and scalability of AIGGC across two design scales. Under the same iteration budgets, AIGGC significantly enhanced three SBO algorithms, i.e., RBFOpt, CMAES, and GA, by 0.62∼0.67% less energy use intensity and 2.14∼4.74% more direct sunlight hours against the baseline solutions, respectively. The contribution of this study involves two aspects, including introducing a novel information-theory-based method for optimizing design parameters in high-dimensional SBO tasks of sustainable building designs, and a novel perspective in guiding stakeholders with interpretable analysis of building design parameters.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112788"},"PeriodicalIF":7.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-way coupled numerical simulation between outdoor thermal environment and PM2.5 in urban blocks","authors":"Meilin Wang ,&nbsp;Hang Ma ,&nbsp;Xing Zheng ,&nbsp;Chun Han ,&nbsp;Pengyuan Shen","doi":"10.1016/j.buildenv.2025.112821","DOIUrl":"10.1016/j.buildenv.2025.112821","url":null,"abstract":"<div><div>While recent studies have explored the influence of outdoor thermal environment parameters on the dispersion of fine particulate matter (PM_2.5), or conversely the impact of PM_2.5 on urban thermal balance, integrated models that quantify the bidirectional feedback mechanisms between these factors are rarely discussed. This research developed a two-way coupled (TWC) numerical model that integrates the thermal environment and PM_2.5 in urban blocks. The proposed model establishes the two-way interactions by coupling momentum exchange between PM_2.5 and airflow speed using the discrete phase model (DPM) and the coupling heat balance between PM_2.5 concentration and thermal radiation using the discrete ordinates (DO) model. The simulation results of the TWC model, validated against actual measurement data, yielded average coefficients of determination (R²) of 0.81 for air temperature, 0.73 for wind speed, and 0.79 for PM_2.5 concentration. To evaluate the effectiveness of our model, we also constructed two \"one-way coupled\" models, which consider the unidirectional influence, and the traditional uncoupled model that neglects these interactions. Numerical simulation results indicated that the TWC model reduced the root mean square error (RMSE) of air temperature, wind speed, and PM_2.5 concentration by 0.12 °C (0.28 %),0.02 m/s (89.67 %),2.74 μg/m³ (24.22 %) compared to the non-coupled model, respectively.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112821"},"PeriodicalIF":7.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embodied carbon in mechanical, electrical, and plumbing systems: A critical literature review","authors":"Matt Roberts ,&nbsp;Claudiane Ouellet-Plamondon ,&nbsp;Paul Raftery","doi":"10.1016/j.buildenv.2025.112823","DOIUrl":"10.1016/j.buildenv.2025.112823","url":null,"abstract":"<div><div>The environmental impacts of mechanical, electrical and plumbing (MEP) systems have been largely overlooked and are commonly excluded from building-scale life cycle assessments (LCAs). Understanding the impacts and reduction potential of these systems is crucial for decarbonizing retrofits and new buildings. Therefore, we have conducted a critical review of LCA studies on MEP systems in buildings, selected using a systematic method, to identify: 1) estimates for upfront embodied [A1-A5] and replacement [B4] carbon impacts; 2) LCA reporting fundamentals needed to ensure transparency and interpretability of results; 3) future research directions. Since 2016, 54 studies presented sufficient information to investigate presented methodologies and LCA results of MEP systems. The review reinforces the need to report environmental impacts by individual life cycle stages and building or system elements to interpret influencing factors and enable further utility of results. Two studies did not report the impact assessment method nor background dataset used for the assessment rendering their results incomparable with others and are excluded from analysis. Based on the median (and mean) of the reviewed studies, estimates for A1-A3 and A1-A5 of the MEP systems are 40 (49) and 49 (61) <span><math><mrow><mi>k</mi><mi>g</mi><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub><mi>e</mi><mo>/</mo><mi>m</mi><mi>²</mi></mrow></math></span>, respectively. Additionally, based on reviewed studies, the systems will be replaced at least twice throughout a 60-year reference study period leading to approximately 100 <span><math><mrow><mi>k</mi><mi>g</mi><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub><mi>e</mi><mo>/</mo><mi>m</mi><mi>²</mi></mrow></math></span> for B4. These values almost certainly underestimate actual impacts due to the incomplete physical scopes spanned by the studies. Studies with more complete scopes generally reported higher values. The variability in scopes covered, reporting practices, and values reported, and the relatively small number of studies found, highlight the need for further investigation and improvement. Ten key research needs are identified, including the impact reduction potential of MEP systems and the influence of system layout and typology on the reported impacts. Additionally, future research should develop system specific benchmarks and reduction strategies while moving away from purely descriptive studies that report environmental impacts using single-point values.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112823"},"PeriodicalIF":7.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling sunlight and shading distribution on 3D trees and buildings: Deep learning augmented geospatial data construction from street view images","authors":"Shu Wang ,&nbsp;Rui Zhu ,&nbsp;Yifan Pu ,&nbsp;Man Sing Wong ,&nbsp;Yanqing Xu ,&nbsp;Zheng Qin","doi":"10.1016/j.buildenv.2025.112816","DOIUrl":"10.1016/j.buildenv.2025.112816","url":null,"abstract":"<div><div>In complex urban environments, accurately estimating the shading effects of trees on three-dimensional (3D) building surfaces is crucial to facilitate building design and urban greenery implementation. However, there is a long-unsolved challenge in efficiently and elaborately modelling trees and simulating spatiotemporally heterogeneous shading effects of trees on 3D urban envelopes. To overcome the challenge, this study proposes a research framework that: (i) employs transfer learning to build a deep learning model for accurately segmenting geo-objects in Street View Images (SVIs), (ii) utilizes semantic segmentation results to fit regressions between the pixels of specific geo-objects in the SVIs and the corresponding real-world lengths of standard geo-objects, develops a 3D space geometric projection model for calculating tree coordinates and 3D geometries, and identifies the real spatial relationships between buildings and trees to calibrate errors caused by segmentation inaccuracies for subsequent simulations, and (iii) integrates the calibrated 3D tree models with 3D building models to construct a unified 3D urban model for estimating the spatiotemporal distribution of sunlight and shading. Using Singapore as the study area, we adopted DeepLabV3+, a widely used pre-trained semantic segmentation model, to achieve IoU of 91.51 % for buildings and 76.29 % for trees, with F1-scores of 97.93 % and 88.19 % respectively. Additionally, data calibration optimized initial tree polygons in 39.03 % of the SVIs, reducing outliers and improving modeling accuracy and robustness. The results demonstrate that the proposed framework efficiently and accurately models high-density urban environments, providing a practical solution to complex shading problems and reducing data acquisition and processing costs.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112816"},"PeriodicalIF":7.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing ventilation and sound insulation in windows by means of metamaterials: A review of the state of the art","authors":"Chiara Rubino ,&nbsp;Stefania Liuzzi ,&nbsp;Gioia Fusaro ,&nbsp;Francesco Martellotta ,&nbsp;Chiara Scrosati ,&nbsp;Massimo Garai","doi":"10.1016/j.buildenv.2025.112780","DOIUrl":"10.1016/j.buildenv.2025.112780","url":null,"abstract":"<div><div>In buildings, natural ventilation plays a major role in ensuring satisfactory indoor air quality levels, but increased noise levels due to urban noise may become an unwanted side effect. Hence, optimizing at the same time both noise reduction and ventilation represents a challenge in the sustainable design of innovative windows. A comprehensive understanding of the current state of the art, the design criteria most frequently used, and the correlations existing between the acoustic and ventilation performances is an essential step towards the development of window solutions for an efficient building envelope. Among the possible solutions, metamaterials offer new opportunities and customized solutions to solve this issue. This review aims to provide an accessible and updated overview of the criteria to adopt when developing efficient windows, focusing on metamaterial applications for designing innovative components able to promote effective ventilation simultaneously with sound attenuation. A total of 56 studies were reviewed to identify current research trends to address sound insulation and ventilation in windows using conventional approaches and metamaterials. The main streams of current research, the knowledge gaps, and the areas still to be explored are finally highlighted.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112780"},"PeriodicalIF":7.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ten questions concerning living laboratories (LL) for multi-domain comfort investigations","authors":"Anna Laura Pisello ,&nbsp;Toka M. Amer ,&nbsp;Benedetta Pioppi","doi":"10.1016/j.buildenv.2025.112750","DOIUrl":"10.1016/j.buildenv.2025.112750","url":null,"abstract":"<div><div>Living labs (LLs) have proven to be powerful tools for evaluating and optimizing human-building interactions to improve comfort, health, and energy savings, particularly resonating with recent multi-domain investigations in buildings. A Living lab for human-centric comfort investigations is a conventional physical space equipped with measurement tools (i.e., sensors, automation and control systems, Building Management systems (BMS) etc.), where occupants carry out day-to-activities, simulating real-world environments for extended periods to study interactive effects of environmental conditions across multiple, or all, aspects of Indoor Environmental Quality (IEQ). By bridging the gap between controlled chamber studies and real-world field studies, Living Labs offer unique opportunities for research. This 10 questions paper is aimed at offering a new and comprehensive perspective on the status of living labs for multi-domain environmental comfort by systematically addressing 10 key questions, providing a clear identification of what qualifies as a <em>Living Lab</em> and distinguishing it from other exploratory approaches. It offers insights into largely unexplored areas, such as distinctions between academic and non-academic LLs, the economic and practical advantages of LLs for non-academic institutions, and the role of emerging technologies. By identifying their key limitations and challenges, the paper highlights the need for actionable recommendations and emphasizes the transformative potential of Living Labs in advancing multi-domain comfort research. Finally, it outlines pathways for the transferability of scalable and sustainable outcomes from Living Lab research into broader real-world applications.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"276 ","pages":"Article 112750"},"PeriodicalIF":7.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating infrared facial thermal imaging and tabular data for multimodal prediction of occupants' thermal sensation","authors":"Haifeng Lan ,&nbsp;Huiying (Cynthia) Hou ,&nbsp;Man Sing Wong","doi":"10.1016/j.buildenv.2025.112814","DOIUrl":"10.1016/j.buildenv.2025.112814","url":null,"abstract":"<div><div>Developing robust thermal comfort models is essential for occupant-centric control (OCC) to optimize the indoor thermal environment while minimizing energy consumption. Conventional single-modal machine learning models, relying solely on either tabular or image data, often suffer from limited prediction accuracy and versatility. To address these challenges, this study proposes a multimodal framework that integrates both data types. A dataset of 610 paired records, encompassing environmental data, individual attributes, thermal sensation votes (TSV), and occupants’ facial thermal images, was collected. Separate single-modal models were trained on tabular and image data to identify the best-performing model for each modality. These were subsequently integrated using a self-attention mechanism to develop a unified multimodal predictive model. Results demonstrate that the artificial neural network (ANN), utilizing only tabular data, achieved an accuracy of 69.67% without incorporating temperature variables from facial regions of interest (ROIs), increasing to 72.46% when these variables were included. Conversely, the Inception-V3 model, trained solely on facial thermal images, achieved 63.44% accuracy. By integrating these approaches, the ANN+Inception-V3 multimodal model achieved a significantly improved accuracy of 81.48%, effectively capturing interaction effects from both data types. This study presents a robust framework and methodological reference for advancing multimodal thermal comfort prediction models, enabling scalable, personalized, and energy-efficient management strategies for indoor environments.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112814"},"PeriodicalIF":7.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of temperature and interior ambient lighting color on nighttime driving performance","authors":"Chao Wang ,&nbsp;John Elson ,&nbsp;Yingzi Lin ,&nbsp;Shichao Liu","doi":"10.1016/j.buildenv.2025.112815","DOIUrl":"10.1016/j.buildenv.2025.112815","url":null,"abstract":"<div><div>Interior ambient lighting has been applied in high-end vehicles to improve driving experience and emotion, owing to the drivers’ perceptions of interior spaciousness and ability to control the vehicle interior environment. Although the influence of temperature and lighting is well-documented in buildings, their effects on driving remain underexplored. Drawing on the hue-heat hypothesis, this study examines the impact of ambient temperatures and interior lighting conditions on driving performance and environmental perception, focusing on their independent and interactive effects. Seventy-two drivers were randomly assigned to three temperature groups (18°C, 23°C, and 28°C) and completed driving tasks in a high-fidelity simulator under varying interior lighting conditions (red, blue, warm white, and cool white). Performance was assessed alongside secondary tasks to simulate real-world driving distractions. Post-task surveys gauged sleepiness, environmental satisfaction, task load, and emotional state. The results show that temperature significantly affects driving performance, cognitive tasks, and environmental perception. Moderate temperatures were preferred for comfort, while higher temperatures impaired accuracy and increased cognitive strain. Metrics like pitch, speed variability, and gas pedal usage were also temperature sensitive. Conversely, lighting condition did not significantly influence driving performance, cognitive tasks, or environmental perception, providing no evidence to support the hue-heat hypothesis. Furthermore, no significant interaction effects were found between temperatures and lighting conditions on any of these metrics, confirming their independent impact. The study underscores the significant role of temperature in influencing driving behavior and perception, while confirming that non-significant effect of lighting condition on driving performance.</div></div>","PeriodicalId":9273,"journal":{"name":"Building and Environment","volume":"275 ","pages":"Article 112815"},"PeriodicalIF":7.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}