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Effectively identifying urban polycentric spatial structure (UPSS) is essential for data-driven evaluation of urban performance, and it serves as a scientific basis for urban spatial planning. However, existing identification methods have limitations such as subjectivity, poor spatial continuity, and a narrow application scale. Thus, from a morphology perspective, our study proposed a rapid, highly applicable, and spatiotemporally comparable nonparametric approach for detecting morphological urban polycentric spatial structure (MUPS) by integrating remote sensing nighttime light (NTL) and point of interest (POI) data. Taking China as an object, on the basis of recognizing urban entities using NTL data, a wavelet transform was initially introduced to fuse multi-source geospatial data, thereby enhancing the spatial intricacy within a city. Then, a local spatial autocorrelation model was utilized to identify pixel clusters. Finally, post-processing was performed to optimize urban centers, subsequently calculating MUPS. Results reveal that urban entities identified based on NTL have a significant advantage in characterizing the concentration of human activities, which can ensure the accuracy of extracting MUPS. Compared with existing relevant methods, the proposed nonparametric approach avoids the misalignment of multi-temporal urban center distribution, enhancing accuracy and stability. Differentiated spatiotemporal patterns were found in the evolutionary trajectories of MUPS in China, with a progressive intensification in the degree of spatial decentralization. Our study provides valuable insights into spatiotemporal analyses of MUPS at multiple scales and serves as a foundational resource for urban spatial planning.

The highly active and selective oxygen reduction reaction (ORR) is vital to promote the performance of advanced energy conversion systems, such as fuel cells and other electrochemical devices. Porous framework materials have the capability to combine the catalytic performance of catalytic active units with their porous characteristics, making them promising oxygen reduction catalysts. However, due to the difficulty in designing and synthesizing catalytic active units, the pore size modulation of framework materials is primarily achieved by altering the linkers. We herein report the design and synthesis of three cobalt-corrole-based porous organic polymers (Co-POP-1, Co-POP-2 and Co-POP-3) with different pore sizes, which were obtained by extending 5,15-meso substituents of Co corroles. Compared to Co-POP-1 and Co-POP-2, Co-POP-3 has the largest pore size. Benefiting from the enhanced mass transfer and the highly exposed active sites, Co-POP-3 displayed remarkably boosted activity for the selective four-electron/four-proton (4e−/4 H+) ORR with a half-wave potential of E1/2 = 0.89 V versus reversible hydrogen electrode (RHE) in 0.1 M KOH solutions. This work not only presents a cobalt-corrole-based porous organic polymer catalyst with high ORR activity and selectivity but also provides a new strategy to moderate the pore size of porous framework materials.

Background: Starting from 2009, H1N1 has been one of the respiratory diseases that afflict the global population. Concurrently, due to the influence of COVID-19, it has become widely accepted that preventing the virus's spread necessitates personal protection measures and disinfection in public spaces. Experiments: This study conducted two experiments. In the classroom experiment, six UVC dose test points were calibrated to test whether the UVC dose at each testing point met the standards for inactivating IAVs and the time required to meet the standards. In the simulated classroom experiment, seven square slides made of IAVs were placed. After 10 min of robot movement, irradiated sterile square slides were made into suspension and injected into chicken embryos. Cultivate chicken embryos and conduct IAVs testing. Results: Classroom experiment has shown that 5 testing points can meet the standards for inactivating IAVs(3 mJ/cm2), with a required time of 80 min, 40 min, 15 min, 5 min and 10 min. The UVC dose for testing points that do not meet the standards in 80 min is only 0.5 mJ/cm2. The simulation classroom experiment outcomes revealed that 99.99 % of IAVs were deactivated. Furthermore, this study established both a desktop control group and a chair arm control group, both of which yielded identical results, indicating an inactivation logarithm of IAVs≥4log. Conclusion: The study presented that IAVs on the surface of an object can be effectively and rapidly deactivated at an irradiation density of 1.8 mW/cm2. Meanwhile, the study provides evidence of the feasibility of using the GXU robot to inactivate IAVs in a classroom environment.

Abstract Tourism eco-efficiency is an important indicator to measure the sustainable development of tourism with the core objective of "minimum resource input and environmental damage, maximum economic and social output". This paper explores the spatial and temporal evolution characteristics of tourism eco-efficiency and its influencing factors in Fujian Province from 2011 to 2020 by combining the unexpected output Super-SBM model, gravity center model, standard deviation ellipse, and optimal parameters-based geographical detector model. The results are as follows. Tourism eco-efficiency in Fujian Province showed an overall fluctuating growth trend with an increase of 160.065% during the study period. The coefficient of variation of tourism eco-efficiency tends to fluctuate and decrease, and regional differences narrow. The spatial differentiation is remarkable, and it presents the spatial distribution characteristics of "Xiamen > Nanping > Quanzhou > Fuzhou > Longyan > Ningde > Sanming > Zhangzhou > Putian". The spatial pattern of tourism eco-efficiency is obvious in the direction of "northeast-southwest", and the trajectory of the center of gravity is "southwest-northeast-northwest", with spatial characteristics tending towards agglomeration. Tourism industry structure has the greatest impact on tourism eco-efficiency, followed by education level, urbanization level, technology innovation level, infrastructure investment, and economic development level. This study provides reference suggestions for improving tourism eco-efficiency which helps to promote adequate, balanced, and sustainable development of the regional tourism industry.

Understanding the relationship between urban development and environmental sustainability to achieve ‘double carbon’ goals in China can be strengthened by evaluating the environmental effect of urban spatial structure (US). However, there have been few studies that consider the differentiated effects of polycentric US (PUS) on carbon emissions from both functional and morphological perspectives simultaneously. Thus, taking China’s 31 provinces as experimental subjects, our study developed a novel framework with remotely sensed nighttime light (NTL) data to quantify morphological PUS (MPUS) and functional PUS (FPUS) from 2000 to 2019. Then, from these two dimensions, differentiated effects of PUS on carbon emissions were further examined. Results indicated that NTL data presented high potential in quantifying MPUS and FPUS. The effect of FPUS on carbon emission-cutting outperformed that of MPUS. In addition, the spillover effect effectively enhanced the decreasing effect of the FPUS on carbon emissions. Our empirical findings can provide guidance for the government in developing strategies for reducing carbon emissions and optimizing USs.

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.

The differences in the definition of urban areas lead to our contrasting or inconsistent understanding of global urban development and their corresponding socioeconomic and environmental impacts. The existing urban areas were widely identified by the boundaries of built-environment or social-connections, rather than urban entities that are essentially the spatial extents of human activity agglomerations. Thus, this study has attempted to map and evaluate global urban entities (2000–2020) from a perspective of an updated urban concept of urban entities based on the consistent remotely sensed nighttime light data. First, a K-means algorithm was developed to cluster urban and non-urban pixels automatically in consideration of global region division. Then, a post-processing was conducted to enhance the temporal and logical consistency of urban entities during the study period. Rationality assessment indicates that urban entities derived from remotely sensed nighttime light data more effectively reflect the spatial agglomeration extents of human activities than those of physical urban areas. Global urban entities increased from 157,733 km2 in 2000 to 470,632 km2 in 2020 accompanied by a differentiated urban expansion at global, continental, and national levels. Our study provides long-time series and fine-resolution datasets (500 m) and new research avenues for spatiotemporal analysis of global urban entity expansion with the improvement of the understanding of urbanization and the emergence of effective urban mapping theories and approaches.

Exploring carbon dioxide (CO2) emissions from human activities is essential for urban energy conservation and resource management. Remotely sensed nighttime lights from the Suomi NPP-VIIRS provide spatial consistency in and a low-cost way of revealing CO2 emissions. Although many researches have documented the feasibility of the Suomi NPP-VIIRS data for assessing CO2 emissions, few have systematically revealed the ability of nighttime lights for evaluating CO2 emissions from different industries, such as service industry CO2 emissions (SC), traffic CO2 emissions (TC), and secondary industry CO2 emissions (IC). Here, China was selected as the experimental subject, and we comprehensively explored the relationships between the nighttime lights and SC, TC, and IC, and investigated the factors mediating these relationships. We found that without considering other factors, the nighttime lights only revealed up to 51.2% of TC, followed by 41.7% of IC and 22.7% of SC. When controlling for city characteristic variables, the models showed that there were positive correlations between the Suomi NPP-VIIRS data and SC, IC, and TC, and that nighttime lights have an Inverted-U relationship with SC. The Suomi NPP-VIIRS data are more suitable for revealing SC, TC, and IC in medium-sized and large-sized cities than in small-sized cities and megacities.

Suburbs, as bridges between urban areas and rural hinterlands, are areas with the most intense urban–rural conflicts and drastic land use changes in the urbanization process. Accurate identification and evaluation of suburbs are important to effectively break the urban–rural dichotomy, improve the utilization and management of land resources, and promote urban–rural integration and coordinated development. Previous suburb identification studies have suffered from low identification efficiency owing to the influence of subjective factors, small scales, short time-series, and single data characteristics. Thus, we took China as experimental object, and attempted to identify suburbs from the Suomi National Polar-orbit Partnership’s Visible Infrared Imaging Radiometer Suite (SNPP–VIIRS) nighttime light remotely sensed data using the K-means algorithm and subsequent series of post-processing approaches. Thereafter, our study further evaluated the spatiotemporal dynamics and driving factors of suburb development. Accuracy verification results show that suburb identification based on SNPP–VIIRS data can identify more details than the existing urban area data and Defense Meteorological Satellite Program’s Operational Linescan System data. Compared with traditional mutation detection methods, the proposed method has the advantages of being fast, efficient, and less subjective. Furthermore, we found that China’s suburbs present a fluctuation-growth trend, with the proportions increasing from 0.6% to 1.3% in the period 2012–2020. China’s suburb development was mainly driven by the development of population density, GDP, and road network. Our study provides an innovative way to conduct a rapid, efficient, and large-scale and accurate suburb identification over a long time series, thereby facilitating the study of socio-environmental issues in the urbanization process. The annual series (2012–2020) of suburbs in China are available free of charge at https://doi.org/10.7910/DVN/M5EED5.

Tourism eco-transformation can provide a long-lasting competitive advantage. However, successful transformation is a challenge for both academia and industry. The literature has focused on the net effect of a single factor. Still, we build on the Technology-Organization-Environment framework and propose that tourism eco-transformation does not depend on a single condition but the configurational effect of organization, environment, and technology. We found six conditions that influence eco-transformation in Chinese provinces. The results show that 1) the tourism eco-transformation in China from 2016 to 2019 “declines first and then rises,” indicating a “U” shape. Spatial distribution is stable; 2) We can classify the high-level transformation model into four configurational types: technology-pulling organization, proactive organization, environmental stress organization, and comprehensive organization. Not-high-level transformation model can be categorized as comprehensive absence and respectable; 3) There are three critical conditions for tourism external connections, environmental regulation, and tourism ecology promotion. In contrast, digital information level, technology innovation capability, and tourism resource endowment are largely determined based on the specific situation. We explore high-level and not-high-level configurational paths of tourism eco-transformation and gain new theoretical insights. We also guide tourism managers to choose or modify high-level tourism eco-transformation paths based on local characteristics to avoid not-high-level tourism eco-transformation situations.

Inconsistent measurements of city-size and a lack of time-series information on urban socioeconomic development have hindered determining whether China's city-size distribution (CD) follows a Pareto distribution according to multiple perspectives. This article has attempted to evaluate China's CD based on the defense meteorological satellite program- operational line-scan system (DMSP-OLS) nighttime light data in terms of socioeconomic size (SS) and spatial size (SC). First, city size was defined from the DMSP-OLS data. Then, whether China's CD followed a Pareto distribution was evaluated from different perspectives. The results show that China's CD from 1995 to 2015 presents a flat distribution trend; the flat distribution trend of the SC is more obvious than that of the SS; “borrowed size” has become an important reason for the flat trend of China's CD; and residential suburbanization, transportation cost reductions, local government policies, and land finances could effectively explain the CD differences in the flat trends between the SS and SC. This article offers an effective means for quantifying and comparing CD in long time series at a large scale (e.g., national scale or regional scale) and provides a scientific decision basis for governments to build a reasonable CD system in China.

Kinkéliba (Combretum micranthum, Seh-Haw in Wolof) is a popular bush tea in West African countries. Although the kinkéliba plant’s leaves have been widely consumed for its nutritional and medicinal properties, its benefits on skin health potential have been practically untouched. In human epidermal primary keratinocytes, vitexin and isovitexin-rich kinkéliba extract treatment significantly (p < 0.001) enhanced up to 39.6% of the cell survival rate decreased by UV radiation irritation. The treatment of kinkéliba leaf extracts also reduced the production of UV-induced pro-inflammatory cytokines IL-6 and IL-8 by 57.6% and 42.5%, respectively (p < 0.001), which cause skin redness and skin barrier dysfunction, as well as wrinkles and collagen degradation. The anti-inflammation efficacy of kinkéliba leaf extracts might involve significant inhibition on the levels of cellular reactive oxygen species (ROS) (−70.8%, p < 0.001) and nitrotyrosine (−56.9%, p < 0.05). Further topical applications of kinkéliba leaf extract gel were found to reduce sodium lauryl sulfate (SLS)-induced skin inflammation: at D7, the skin trans-epidermal water loss (TEWL) and skin redness (a* value) were both reduced by 59.81% (p < 0.001) and 22.4% (p < 0.001), compared with D0. In vitro and in vivo data support a new topical application of the kinkéliba leaf as an effective active ingredient for the treatment of skin inflammation, as well as subsequent barrier dysfunction and inflammaging.

Based on the multi-body dynamics software RecurDyn, a virtual prototype model of new type， RU type and ZA type double helical synchronous belt drive is established, and rigid-flexible coupling motion modeling and dynamic simulation are carried out. Under the same conditions, for the three tooth profiles double helical synchronous belts, the stress distribution cloud diagram of the belt strong layer and the tooth and the stress distribution law of the special point of the tooth root are studied in the fully meshed area, and the study of the stress variation law of special points in the belt movement cycle. In terms of belt drive performance, the law of lateral vibration and tension fluctuation of the belt and the law of angular velocity change of the driven pulley are studied. The results show that the tooth root stress of the double helical synchronous belt is smaller, the bearing capacity is the strongest, and the amplitude of the lateral vibration, tension fluctuation and driven pulley speed fluctuation of the belt is the lowest. It shows that the tooth profile of the double helical synchronous belt and the pulley has good meshing drive performance and smooth movement, and high drive accuracy.

In view of the problem of the GB/T 10414-2017 Synchronous belt drive car synchronous belt pulley standard does not provide the RU type and YU type pulley standard tool tooth profile parameter, the conjugate harmonic relationship between the pulley and tool tooth profile are studied. Firstly, the conjugate tool tooth surface of the pulley tooth profile is enveloped based on the meshing principle, and the discrete data of the envelope curve is mathematically fitted to determine the mathematical model of the cutter tooth profile. Secondly, through the second enveloping process of the cutter on the pulley, it is found that there is an undercut at the top of the tooth profile of the processed pulley tooth profile. Through the study of the mechanism of undercutting, the reason of singularity of cutter surface is revealed, and tooth profile model to eliminate the singular point of cutter tooth profile curve is proposed. The tooth profile error based on pulley is within the standard tolerance range, the cutter parameter is redesigned.

The regional disparity of urban expansion varies significantly in China’s different regions, hindering sustainable socioeconomic development. However, most studies to date have focused on a single aspect of urban expansion, e.g., urban spatial expansion (USS) disparity. This study attempts to define urban expansion from USS and urban socioeconomic expansion (USE) based on nighttime light remotely sensed (NTL) data and urban land datasets. Then, taking China’s 241 prefecture-level cities within different provinces as experimental subjects, the Dagum Gini (DG) coefficient and stochastic convergence test are employed to assess the disparity of urban expansion from two different dimensions. The results show that, on the national scale, the regional disparity of USS is always greater than that of USE and has a converging trend. Additionally, regional disparity is the main factor causing the difference between USS and USE, with average contribution rates of 55% and 45%, respectively. The average difference between USS and USE in the eastern region (ER) is greater than 10%, while it is the lowest in the northeastern region (NER) and shows a significant expansion trend in performance convergence with a regression coefficient of 0.0022, followed by the central (CR), eastern, and western (WR) regions. Through the panel unit root test, we found that urban expansion in China in terms of USS and USE has internal random convergence in certain regions under the premise of global random divergence, and there may be differentiation and formation of one or more convergence clubs in the future. Using this novel perspective to define urban expansion, this study quantifies the contributions of USS and USE to regional disparity and provides a scientific basis for governments to implement appropriate approaches to sustainable urban development in different regions.

There is no consensus on the effect of China’s rapid urban expansion on the fine particulate matter (PM2.5) emissions from fossil fuel combustion (PC). Previous studies usually focused on the environmental effect of urban expansion from a single mode (e.g., spatial expansion). However, studies that simultaneously considered and compared the effect from spatial and socioeconomic modes are still lacking. Thus, we combined multiple data sources (e.g., nighttime light data, urban land datasets, and PC) and econometric methods to evaluate the effect of urban expansion on PC within different regions from spatial and socioeconomic modes. The results show that China’s urban socioeconomic expansion (UE) and urban spatial expansion (US) increased from 68.50% and 11.81 × 10−4, respectively, in 1992 to 72.23% and 66.86 × 10−4, respectively in 2012. The UE is the Granger cause of the increased PC in China. Through variance decomposition analysis, we also found that the UE contributed much more to the PC in China than the US. When comparing the different regions, we recognized that the UE was the key factor in explaining the increase in the PC in the eastern and northeastern regions, and the US could effectively explain the changes in the PC in the central region. The study provides a novel perspective for quantifying the effect of urban intensive and extensive development on haze pollution.

Virtual machine (VM) re-deployment and migration has been proven to be a key technique for cloud data centers to implement resource optimization and load balance. Also, live VM migration aims to guarantee the continuity of the existing data flows. Though VM management has been well studied, it has so far mostly focused on optimizing resource utilization, while the important issue of users' quality of experience has been ignored. In mobile cloud computing, user distribution changes dynamically over time and it can significantly affect both the service latency and network resource utilization. In the traditional network, VM migration may cause a flash crowd of flow changing and a long service downtime due to VM's IP address changing. Software-defined networking is an emerging paradigm to logically centralize the network control plane and automate the configuration of individual network elements, which can be ubiquitously deployed in data centers and serve as an effective means for flow handling. In this paper, we design a user distribution-aware virtual machine re-deployment mechanism and propose a traffic-redirection virtual machine migration scheme to keep the active flows from being interrupted. We further provide simulations to show the effectiveness and superiority of the proposed approaches over existing schemes.

A low-grade pro-inflammatory state is at the pathogenic core of obesity and type 2 diabetes. We tested the hypothesis that the plant terpenoid compound ginsenoside Rb1 (Rb1), known to exert anti-inflammatory effects, would ameliorate obesity, obesity-associated inflammation and glucose intolerance in the high-fat diet-induced obese mouse model. Furthermore, we examined the effect of Rb1 treatment on central leptin sensitivity and the leptin signaling pathway in the hypothalamus. We found that intraperitoneal injections of Rb1 (14 mg/kg, daily) for 21 days significantly reduced body weight gain, fat mass accumulation, and improved glucose tolerance in obese mice on a HF diet compared to vehicle treatment. Importantly, Rb1 treatment also reduced levels of pro-inflammatory cytokines (TNF-α, IL-6 and/or IL-1β) and NF-κB pathway molecules (p-IKK and p-IκBα) in adipose tissue and liver. In the hypothalamus, Rb1 treatment decreased the expression of inflammatory markers (IL-6, IL-1β and p-IKK) and negative regulators of leptin signaling (SOCS3 and PTP1B). Furthermore, Rb1 treatment also restored the anorexic effect of leptin in high-fat fed mice as well as leptin pSTAT3 signaling in the hypothalamus. Ginsenoside Rb1 has potential for use as an anti-obesity therapeutic agent that modulates obesity-induced inflammation and improves central leptin sensitivity in HF diet-induced obesity.

Bornyl gallate (BG) is a potential drug candidate synthesized by the reaction of two natural products, gallic acid and borneol. Previous studies have strongly suggested that BG is worthy of further investigation due to antioxidant, antiatherosclerosis activities, and obvious activity of stimulating intersegmental vessel growth in zebrafish. This work was designed to elucidate the metabolic profile of BG through analyzing its metabolites in vitro and in vivo by a chromatographic separation coupled with a mass spectrometry. The metabolites of BG were characterized from the rat liver microsome incubation solution, as well as rat urine and plasma after oral administration. Chromatographic separation was performed on an Agilent TC-C18 column (250 mm × 4.6 mm, 5 μm) with gradient elution using methanol and water containing 0.2% (V : V) formic acid as the mobile phase. Metabolites identification involved analyzing the retention behaviors, changes of molecular weights and MS/MS fragment patterns of BG and the metabolites. Five compounds were identified as isomers of hydroxylated BG metabolites in vitro. The major metabolites of BG in rat urine and plasma proved to be BG-O-glucuronide and O-methyl BG-O-glucuronide. The proposed method confirmed to be a reliable and sensitive alternative for characterizing metabolic pathways of BG.

BACKGROUND: G-protein coupled receptors (GPR) bear the potential to serve as yet unidentified drug targets for psychiatric and metabolic disorders. GPR12 is of major interest given its putative role in metabolic function and its unique brain distribution, which suggests a role in emotionality and affect. We tested Gpr12 deficient mice in a series of metabolic and behavioural tests and subjected them to a well-established high-fat diet feeding protocol. METHODOLOGY/PRINCIPAL FINDINGS: Comparing the mutant mice with wild type littermates, no significant differences were seen in body weight, fatness or weight gain induced by a high-fat diet. The Gpr12 mutant mice displayed a modest but significant lowering of energy expenditure and a trend to lower food intake on a chow diet, but no other metabolic parameters, including respiratory rate, were altered. No emotionality-related behaviours (assessed by light-dark box, tail suspension, and open field tests) were affected by the Gpr12 gene mutation. CONCLUSIONS/SIGNIFICANCE: Studying metabolic and emotionality parameters in Gpr12 mutant mice did not reveal a major phenotypic impact of the gene mutation. Compared to previous results showing a metabolic phenotype in Gpr12 mice with a mixed 129 and C57Bl6 background, we suggest that a more pure C57Bl/6 background due to further backcrossing might have reduced the phenotypic penetrance.

Developing electrocatalysts with high activity and selectivity for the oxygen reduction reaction (ORR) is vital to promote the performance of the next-generation energy technologies, which depend on the efficiency of the catalytic reduction of dioxygen. In the structure of cytochrome c oxidases (CcOs), a histidine imidazole residue binding to the axial position of Fe plays a crucial role in facilitating the selective reduction of O2 to water. Inspired by nature, we herein report on the synthesis of CoIII corrole 1 tethered with an imidazole ligand as well as its electrocatalytic ORR and O2 binding features. As compared to the imidazolium-free analogue, complex 1 displayed remarkably boosted activity for the selective four-electron/four-proton (4e-/4H+) ORR with a half-wave potential of E1/2 = 0.82 V versus reversible hydrogen electrode (RHE) in 0.1 mol/L KOH solutions. Importantly, we demonstrate that the tethered axial imidazole ligand improves the O2 binding ability of 1 thermodynamically and dynamically, which is crucial to boost electrocatalytic ORR performance. This work presents an example to improve electrocatalytic ORR activity and selectivity of Co corroles by introducing an axial imidazole ligand to enhance the O2 binding and activation. [ABSTRACT FROM AUTHOR]

Highly oxygenated organic molecules (HOMs) can participate in new particle formation (NPF) and enhance growth of newly formed particles partially because of their low volatility. Previous studies have shown formation of HOMs via autoxidation reactions of RO2 intermediates generated by OH-initiated oxidation of anthropogenic volatile organic compounds (VOCs). It was also suggested that multi-generation OH oxidation could be an important source for aromatics-derived HOMs. However, our understanding on the generation of aromatics-derived HOMs are still insufficient, especially for their formation mechanisms, which determine molar yields of HOMs and are essential to the establishment of global chemical box models related to HOMs. In this study, with a potential aerosol formation oxidation flow reactor (PAM OFR), a series of OH-initiated oxidation experiments of 1,3,5-trimethylbenzene (1,3,5-TMB) were conducted to investigate the influences of the extent of OH exposure on the formation of aromatics-derived HOMs. The evolution of oxidation products of 1,3,5-TMB in an OH exposure range of (0.5 - 5.0)×1010 molecules cm-3 s, equivalent to an OH exposure of 0.7 - 6.9 hours at an OH concentration of 2×106 molecules cm-3, was investigated by a nitrate-based chemical ionization mass spectrometer and a Vocus proton-transfer-reaction mass spectrometer, indicating significant secondary OH chemistry during the ageing of stabilized first generation oxygenated products within an intraday OH exposure and formation of various HOMs with more oxygen content and thus lower volatility. In addition, organonitrates, formed after the introduction of NOx into the reaction systems, further confirmed the existence of such secondary reactions. Our study suggests an important role of secondary OH chemistry in the oxidation of aromatics and elucidates detailed formation mechanisms of certain HOM products. [ABSTRACT FROM AUTHOR]