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In the modern financial market, quantitative investment is a more advanced investment method, which has been widely used in the capital market with the characteristics of simplicity, efficiency, and plasticity. Compared with other countries, China started late in the quantitative field, and the strategies are not perfect enough to be studied in depth. To study quantitative investment in-depth, this paper proposes a GA-VMD-SSA-DELM quantitative model. By building an extreme learning machine (DELM) model optimized by the sparrow algorithm (SSA), and simultaneously using a variational modal decomposition model (VMD) optimized by the genetic algorithm (GA) for data noise reduction, a quantitative investment model is constructed, and a portfolio strategy is formed. The method first performs correlation tests on the data sources, uses the daily frequency trading indicators of Guizhou Maotai, Zhifei Bio, and Yangtze River Power for the years 2018-2022 as the database, and uses SPSS to conduct Pearson correlation coefficient analysis to establish the correlation between the data. Then the GA-VMD algorithm was used for data noise reduction. Finally, the SSA-DELM algorithm is used to establish a quantitative investment model, construct a portfolio, and draw relevant conclusions.

This research has been supported by the European Research Council (GC2.0 (grant no. 694481)), the European Research Council (REALM (grant no. 787203)), Imperial College through the Lee Family Scholarship, the Leverhulme Centre for Wildfires, Environment and Society (grant no. RC-2018-023), and the REDISCO (grant no. HAR2017-88035-P) project., Charcoal accumulated in lake, bog or other anoxic sediments through time has been used to document the geographical patterns in changes in fire regimes. Such reconstructions are useful to explore the impact of climate and vegetation changes on fire during periods when human influence was less prevalent than today. However, charcoal records only provide semi-quantitative estimates of change in biomass burning. Here we derive quantitative estimates of burnt area from vegetation data in two stages. First, we relate the modern charcoal abundance to burnt area using a conversion factor derived from a generalised linear model of burnt area probability based on eight environmental predictors. Then, we establish the relationship between fossil pollen assemblages and burnt area using tolerance-weighted weighted averaging partial least-squares regression with a sampling frequency correction (fxTWA-PLS). We test this approach using the Iberian Peninsula as a case study because it is a fire-prone region with abundant pollen and charcoal records covering the Holocene. We derive the vegetation-burnt area relationship using the 31 records that have both modern and fossil charcoal and pollen data and then reconstruct palaeoburnt area for the 113 records with Holocene pollen records. The pollen data predict charcoal-derived burnt area relatively well (R-2 = 0.44), and the changes in reconstructed burnt area are synchronous with known climate changes through the Holocene. This new method opens up the possibility of reconstructing changes in fire regimes quantitatively from pollen records, after regional calibration of the vegetation-burnt area relationship, in regions where pollen records are more abundant than charcoal records., European Research Council (ERC) European Commission 694481 787203, Imperial College through the Lee Family Scholarship, Leverhulme Centre for Wildfires, Environment and Society RC-2018-023 REDISCO HAR2017-88035-P

Objective We investigated the pathogenesis of a patient with severe acute pancreatitis by comprehensively analysing a rare carbapenem-resistant hypervirulent K1/ST1265 Klebsiella pneumoniae (CR-HvKP) strain. Methods We conducted virulence and multidrug-resistance phenotypic characterization and identified a CR-HvKP strain from the patient. It was subjected to Pacbio sequencing, and subsequent analysis of virulence, resistance genes and mobile genetic elements. Results We described the phenotype and genotype of a rare CR-HvKP strain with an untypeable blaKPC-harboured conjugative plasmid and a pLVPK-like virulent plasmid. Resistance gene analysis showed that the untypeable blaKPC-2-harboured plasmid was formed by IS26-mediated recombination of blaKPC-embedded transposon Tn6500 into pCN061p4 from Escherichia coli. Interestingly, it had an R-M system that might protect plasmid from cleavage. This may facilitate the stabilization of plasmids in bacteria in the event of missing CR-plasmid during transmission. Virulence gene analysis indicated 78 virulence genes on the genome, including 67 on the chromosome (37 in high-pathogenic island) and 11 on the pLVPK-like virulence plasmid (harbouring rmpA/rmpA2). Further phylogenetic analysis revealed that the CR-HvKP evolved from HvKP through acquiring an antimicrobial-resistance plasmid. Conclusion Our research, to our knowledge, first reported a ST1265/K1 CR-HvKP strain with an untypeable blaKPC-harboured plasmid. The trend that HvKP could evolve into CR-HvKP by obtaining stabilized/conjugative blaKPC-carrying plasmids is a considerable threat to public health and should be closely supervised.

Plants in fire-prone ecosystems have evolved a variety of mechanisms to resist or adapt to fire. Post-fire resprouting is a key adaptation that promotes rapid ecosystem recovery and hence has a major impact on the terrestrial carbon cycle. However, our understanding of how the incidence of resprouting varies in different fire regimes is largely qualitative. The increasing availability of plant trait data and plot-based species cover data provides an opportunity to quantify the relationships between fire-related traits and fire properties. We investigated the quantitative relationship between fire frequency (expressed as the fire return time) and the proportion of resprouters in woody plants using plot data on species cover from Australia and Europe. We also examined the relationship between the proportion of resprouters and gross primary production (GPP) and grass cover, where GPP was assumed to reflect fuel loads and hence fire intensity, while grass cover was considered to be an indicator of the likelihood of ground fire and the speed of fire spread, using generalised linear modelling. The proportion of resprouting species decreased significantly as the fire return time increased. When the fire return time was considered along with other aspects of the fire regime, the proportion of resprouters had significant negative relationships with the fire return time and grass cover and a significant positive relationship with GPP. These findings demonstrate that plants with the ability to resprout occur more often where fire regimes are characterised by high-frequency and high-intensity crown fires. Establishing quantitative relationships between the incidence of resprouting and the fire return time and fire type provides a basis for modelling resprouting as a consequence of the characteristics of the fire regime, which in turn makes it possible to model the consequences of changing fire regimes on ecosystem properties.

By expounding and proving the technical background of and demand for the platform for the take-off and landing of unmanned aerial vehicles (UAVs), and by analyzing the necessity in combination with current domestic and overseas situations, this paper reveals how a vehicle-mounted platform for take-off and landing of UAVs consisting of multiple connecting rods was developed. Meanwhile, the feasibility of the technology of the vehicle-mounted platform for take-off and landing consisting of multiple connecting rods was verified from multiple aspects by utilizing precision transmission technology, a general mechanical model, and a proof-of-principle prototype.

Fire is a major disturbance in natural ecosystems and more extreme fires are predicted to occur in the future. Plant species can survive or resist wildfires and adapt to fire-prone regimes by exhibiting fire-related plant traits such as serotiny and heat-simulated germination. Resprouting is one of the most common plant traits that confer resilience to fire, promoting rapid post-fire recovery and affecting ecosystem dynamics. We investigated the relationships between the abundance of resprouting woody species, fire return interval and fire intensity in three regions: Europe, Australia and South and Central America. Species abundance data were obtained from the SplotOpen database while resprouting information are derived from regional and global databases, field information and the literature. Fire return time and fire intensity at each site were estimated using remotely sensed observations (MODIS MCD64CMQ, MODIS MCD14ML and Fire Atlas). We show that the abundance of resprouting woody species decreases with increasing fire return interval but that resprouters are most abundant at intermediate levels of fire intensity. These patterns are seen in all the three regions. Given that the abundance of resprouting woody species is strongly related to the fire regime, it should be possible to model their distribution in an optimality framework. Since the abundance of resprouters will affect ecosystem post-fire recovery, it is important to include this trait in fire-enabled vegetation models in order to simulate ecosystem dynamics adequately.

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. The Reading Palaeofire Database (RPD) represents the most comprehensive compilation of sedimentary charcoal data currently available. It contains 1673 individual charcoal records from 1480 sites worldwide, with sufficient metadata to allow for the appropriate selection of sites to address specific questions. Most of the records have new age models, made by re-calibrating the radiocarbon ages using INTCAL2020 and Bayesian age-modelling software. In this talk we will show how these data are being used to document changing fire regimes during the Late Quaternary and to explore how fire regimes have responded to changes in climate, vegetation and human activities. We will demonstrate the progress that has been made to calibrate the charcoal records and make quantitative estimates of fire properties. We will also explore how these data can be used to evaluate and benchmark process-based fire-enabled models. Finally, we will highlight opportunities to use the palaeo-record together with models to explore fire regimes and their consequences for land-surface processes, biogeochemical cycles and climate.

This research has been supported by the Leverhulme Trust (grant no. RC-2018-023), the European Research Council (grant no. 694481), the German Research Foundation (grant no. FE-1096/6-1), the Swiss Government Excellence Postdoctoral Scholarships (grant no. FIRECO 2016.0310), the National Science Centre of Poland (grant no. 2015/17/B/ST10/01656), the SCIEX Scholarship Fund (grant no. PSPB-013/2010), and the Estonian Research Council (grant no. MOBJD313)., Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b – Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345., Leverhulme Trust RC-2018-023, European Research Council (ERC) European Commission 694481, German Research Foundation (DFG) FE-1096/6-1, Swiss Government Excellence Postdoctoral Scholarships FIRECO 2016.0310, SCIEX Scholarship Fund PSPB-013/2010, Estonian Research Council MOBJD313

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

Background Colorectal cancer (CRC) is a common gastrointestinal malignant tumor that occurs in the colon site and accounts for 9% of the total malignant tumors. Among malignant tumors, its morbidity and mortality respectively rank third and fourth, seriously threatening human health and causing a heavy economic burden on society. ZIP7 (SLC39A7), a kind of zinc transporter, plays a crucial role in the self-renewal of intestinal epithelial cells; however, its role in CRC has not been extensively examined. Therefore, our study aimed to analyze the biological function and expression of this zinc transporter in CRC, along with its correlation with disease activity. Methods In this study, 118 cases of colorectal carcinoma tissues, 30 normal tissue samples from adjacent cancer tissues, and 30 normal intestinal mucosa tissue samples from non-intestinal cancer patients were collected in our hospital between February 2014 and February 2015. The expressions of ZIP7 were examined immunohistochemically, and the relationship between ZIP7 expression and the clinical pathological features of CRC were analyzed. After appropriate surgical treatment, the patients accepted a 5-year follow-up for evaluation of their recurrence situation and 5-year survival rate. Results Immunohistochemically, out of 80 CRC tissue samples, 67.8% were found to be positive for ZIP7, 55% (44 cases) were strong positives, and 45% (36 cases) were weak positives. There was a striking coherence between the expression of ZIP7, the depth of lymph node metastasis, CRC invasion, and CRC Dukes stage (P

Fire is a common disturbance both from natural source and anthropogenic activities and an important factor in driving the variation of soil organic carbons. A 5-year study was conducted to examine the influence of annual prescribed fire on soil organic carbon (SOC) fraction in a fire-prone plant community, Triarrhena lutarioriparia community, in Poyang Lake, China. The results showed that after burning the contents of dissolved organic carbon (DOC), soil microbial biomass carbon (SMBC) and light fraction organic carbon (LFOC) increased significantly from 78.53 mg/kg to 131.72 mg/kg, 365.58 mg/kg to 603.42 mg/kg, and 14.82 g/kg to 20.56 g/kg, respectively, during the 5-year studying period. On the other hand, the contents of total SOC and heavy fraction organic carbon (HFOC) only increased slightly from 53.67 g/kg to 61.39 g/kg and 33.45 g/kg to 37.46 g/kg, respectively. The results strongly suggested that DOC was more sensitive to the prescribed fire than SOC. Moreover, the annual ratios of DOC, SMBC and LFOC to SOC significantly increased after burn treatments. Taken together, prescribed fire could greatly increase the contents of soil active organic carbons, and enhance the carbon cycle in Poyang Lake. Thus, it could be taken as an exercisable measure to improve the carbon capacity and maintain the soil productivity in the lake wetland.

Haze pollution caused by PM2.5 is the largest air quality concern in China in recent years. Long-term measurements of PM2.5 and the precursors and chemical speciation are crucially important for evaluating the efficiency of emission control, understanding formation and transport of PM2.5 associated with the change of meteorology, and accessing the impact of human activities on regional climate change. Here we reported long-term continuous measurements of PM2.5, chemical components, and their precursors at a regional background station, the Station for Observing Regional Processes of the Earth System (SORPES), in Nanjing, eastern China, since 2011. We found that PM2.5 at the station has experienced a substantial decrease (−9.1 % yr−1), accompanied by even a very significant reduction of SO2 (−16.7 % yr−1), since the national “Ten Measures of Air” took action in 2013. Control of open biomass burning and fossil-fuel combustion are the two dominant factors that influence the PM2.5 reduction in early summer and winter, respectively. In the cold season (November–January), the nitrate fraction was significantly increased, especially when air masses were transported from the north. More NH3 available from a substantial reduction of SO2 and increased oxidization capacity are the main factors for the enhanced nitrate formation. The changes of year-to-year meteorology have contributed to 24 % of the PM2.5 decrease since 2013. This study highlights several important implications on air pollution control policy in China.

Aiming at the characteristics of compact structure, high integration and limited weight and volume of the mobile platform for vehicle-mounted high-power microwave weapon, this paper carried out an integrated design of lifting Jane and lifting electric cylinder. The performance index, system composition and structure design of the tipping lift device are described in detail. Through checking and testing the performance index, the author guarantees that the design is reasonable and feasible. The device runs smoothly after loading. This meets the functional requirements. It can be used as a reference for the subsequent development of radar overturning lifting system under similar conditions.

Phthalate esters (PAEs) as hazardous air pollutants can be easily released during the life cycle of plastic products. In this study, a thermal desorption aerosol comprehensive two-dimensional gas chromatography mass spectrometer coupled with a dual-trap was developed and used to measure the hourly-resolved PAEs characteristics in atmospheric PM

High-emission vehicles (high emitters) likely have significantly higher nitrogen oxide and particle number (PN) emission factors compared to other vehicles. Effective identification of these vehicles in road traffic requires efficient and cost-effective instruments. In this study, a compact, cost-effective sensor platform was developed and evaluated in a field experiment. The platform was deployed on a roadside, and we measured pollutant concentrations in the exhaust plumes of four diesel trucks with various aftertreatment systems, cargo loads, and driving speeds. The sensor platform successfully measured carbon dioxide, PN, and nitric oxide (NO) concentrations, and the data were used to derive the plume-based emission factors of these pollutants. By considering both NO and PN emission factors, three diesel trucks with failed or outdated aftertreatment systems were successfully identified as potential high emitters. The NO emission factor obtained by the sensor platform was consistent with that of the benchmark portable emission measurement system (r = 0.93). The sensor platform also effectively elucidated the differential influences of aftertreatment systems and driving conditions on emission factors. This pilot test demonstrates the feasibility of a sensor-based system for high emitter identification. Owing to its cost-effective and compact design, the proposed sensor platform has greater potential for mass networked deployment than regular-size instruments, thereby effectively supporting regulatory protocols for screening high emitters on public roads.

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using INTCAL2020 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1681 records (entities) from 1477 sites worldwide. The database (DOI: 10.17864/1947.319) is available from https://researchdata.reading.ac.uk/id/eprint/319.

Submicron particles in polluted regions have received much attention because of their influences on human health and climate. A k-means clustering technique was performed on a data set of particle number size distributions (PNSD) that was obtained over more than 3 years in the Yangtze River Delta (YRD) region of East China. With simultaneous measurements of meteorological conditions, trace gases and aerosol compositions, seven clusters were categorized and interpreted. Cluster 1 and cluster 2, which accounted for 9.9% of the total PNSD data, were attributed to new particle formation (NPF) and vehicle exhaust emissions with different intensities; Cluster 3 and Cluster 4, which accounted for 10.5% of the total PNSD data, were related to the growth of nucleation mode particles; Cluster 5, which accounted for 37.9% of the total data, was attributed to the humid YRD background; and Cluster 6 and Cluster 7, which accounted for 41.6% of the total data set, were both pollution-related clusters with similar mass concentrations but completely different PNSD. Although the PM2.5 mass concentrations were somewhat similar, the particle number concentrations of the accumulation mode particles could vary by more than one order of magnitude from the urban background cluster to the pollution-related clusters. The cluster proximity diagram and conversion flow chart of clusters clearly show the influence of NPF and growth on haze, as well as the conversion between background and polluted conditions. This study highlights the importance of PNSD for understanding urban air quality and recommends the clustering technique for analyzing complex PNSD datasets. Plain Language Summary Submicron particles in polluted regions have significant influences on human health and climate. Based on long-term field measurements, we used the k-means clustering technique to characterize the number size distributions of submicron particles in the Yangtze River Delta (YRD) of China. Seven clusters were categorized and interpreted. New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in the YRD. The influences of NPF and growth on haze, as well as the conversion between background and polluted conditions, were found. Key Points New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in Nanjing The influences of NPF and growth on haze, and the conversion between background and pollution conditions were found The k-means cluster technique is an effective tool to categorize particle number size distribution data set

Analyses of the regional controls representing climate, vegetation and human activities on modern burnt area in the Iberian Peninsula show that the vegetation properties that determine fuel availability are major influences on the occurrence of fire. This finding opens up the possibility of using pollen data to reconstruct past changes in fire regimes. We could then make use of the much greater abundance of pollen data compared to other sources of information on past fire regimes to constrain biomass-burning feedbacks to the carbon cycle and climate. We applied Tolerance-Weighted Averaging Partial Least-Squares (TWA-PLS) to derive quantitative relationships between pollen-taxon and charcoal abundances from 15 entities from the Iberian Peninsula, using core-top charcoal data and a generalized linear model of present-day fire probability to provide conversion factors between the relative scale of charcoal abundance and the absolute scale of fire. We show that pollen taxon abundance has good predictive power for fire (r2 = 0.56) and that the contribution of specific taxa to the prediction makes sense in terms of their ecological adaptations to fire. We apply the TWA-PLS quantitative relationship to predict changing fire regimes across the Iberian Peninsula through the Holocene. Results show that fire change synchronous with climate warming events.

We introduce Rabia, a simple and high performance framework for implementing state-machine replication (SMR) within a datacenter. The main innovation of Rabia is in using randomization to simplify the design. Rabia provides the following two features: (i) It does not need any fail-over protocol and supports trivial auxiliary protocols like log compaction, snapshotting, and reconfiguration, components that are often considered the most challenging when developing SMR systems; and (ii) It provides high performance, up to 1.5x higher throughput than the closest competitor (i.e., EPaxos) in a favorable setup (same availability zone with three replicas) and is comparable with a larger number of replicas or when deployed in multiple availability zones., Comment: Full version of the SOSP21 paper

Radioresistance is one of the primary causes responsible for therapeutic failure and recurrence of cancer. It is well documented that reactive oxygen species (ROS) contribute to the initiation and development of gastric cancer (GC), and the levels of ROS are significantly increased in patients with GC accompanied with abnormal expressions of multiple inflammatory factors. It is also well documented that ROS can activate cancer cells and inflammatory cells, stimulating the release of a variety of inflammatory cytokines, which subsequently mediates the tumor microenvironment (TME) and promotes cancer stem cell (CSC) maintenance as well as renewal and epithelial-mesenchymal transition (EMT), ultimately resulting in radioresistance and recurrence of GC.

Haze pollution caused by PM2.5 is the largest air quality concern in China in recent years. Long-term measurements of PM2.5 and the precursors and chemical speciation is crucially important for evaluating the efficiency of emission control, understanding formation and transport of PM2.5 associated with the change of meteorology and for accessing the impact of human activities to regional climate change. Here we reported long-term continuous measurements of PM2.5, chemical components, and their precursors at a regional background station, the Station for Observing Regional Processes of the Earth System (SORPES), in Nanjing eastern China since 2011. We found that PM2.5 at the station has experienced a substantial decrease (−9.1 %/yr), accompanied with even much significant reduction of SO2 (−16.7 %/yr), since the national "Ten measures" for air took action in 2013. Control of open biomass burning and fossil-fuel combustion are the two dominant factors that influence the PM2.5 reduction in early summer and winter, respectively. In cold season (November–January), increased nitrate fraction was observed with more NH3 available from a substantial reduction of sulfate, and the change of year-to-year meteorology contributed to 24 % of the PM2.5 decrease since 2013. This study highlights several important implications on air pollution control policy in China.

In this paper, phosphor silicate glass (PSG) containing CsPbBr3 QDs was prepared by the eutectic method and heat treatment technology. By Using analytical methods including X-ray diffraction, fluorescence testing, and transmission electron microscopy, systematically study the influence of the composition of SiO2 and Al2O3 in the glass matrix on the crystallization and luminescence of QDs, and determine the best raw material composition of CsPbBr3 QD glass (QDG). The results show that the optimal composition ratio of the raw materials is 80NH4H2PO4- 15SiO2- 6SrCO3- 3.4Al2O3- 15Cs2CO3- 7.5PbBr2- 15KBr. The CsPbBr3 QDG made with this raw material composition has the best luminescence performance, which can produce a strong emission peak at 512 nm under the excitation of 390 nm violet light.

Variability of flow is recognized as one of the greatest obstacles to production management. Since the work flow and labour flow are two dominators of work performance, it is important to manage them simultaneously. The objective of this paper is to examine if an increased plan reliability could be reached by reducing the variance of a labour flow. Therefore, three different construction labour data sets have been examined by utilizing Monte Carlo Simulation, to analyze the probability to finish simulated projects within a certain time. The research findings revealed that reducing variance of the workforce flow does not necessarily shorten the project length, nevertheless it increases probability to finish the tasks within a critical path duration. Additionally, it was concluded, that reducing the variance of crew allocation can improve the productivity.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce, there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizatios have been made earlier, in the present work a new one is presented. The relationships between AOPs, NCCN and particle number size distributions were investigated based on in-situ measurement data from six stations in very different environments around the world. The parameterization derived here depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF) and total scattering coefficient (σsp) of PM10 particles. The analysis showed that the dependence of NCCN on supersaturation SS% is logarithmic: NCCN ≈ ((287 ± 45)SAE10ln(SS%/(0.093 ± 0.006))(BSF − BSFmin) + (5.2 ± 3.3))σsp. At the lowest supersaturations of each site (SS% ≈ 0.1) the average bias, defined as the ratio of the AOP-derived and measured NCCN varied from ~ 0.7 to ~ 1.5 at most sites except at a Himalayan site where bias was > 4. At SS% > 0.3 the average bias ranged from ~ 0.7 to ~ 1.3 at all sites. In other words, at SS% > 0.3 NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The squared correlation coefficients between the AOP-derived and measured NCCN varied from ~ 0.5 to ~ 0.8. The coefficients of the parameterization derived for the different sites were linearly related to each other. To study the explanation of this, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation yielded similar relationships between the coefficients as in the field data. It also showed that the relationships of the coefficients are affected by the geometric mean diameter and width of the size distribution and the activation diameter.

In this paper, we present long term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate OMI satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ~ 30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. We developed a new technique to assemble the source contribution map using backward trajectory analysis. The age weighted backward propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward propagated HCHO data does not show a strong spatial correlation with the OMI HCHO observations. The result shows the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants in over the Yangtze River Delta as well as the effect of emission control measures during large international event, which are important for the future design of air pollution control policies.

In order to correctly understand the information about the life of the crane and to promptly eliminate the potential structural safety hazard of the crane, this paper takes the portal crane as an example to build infinite element model. First of all, the static stress analysis is carried out via infinite element software such as Patran and Nastran to obtain the size and location of the maximum equivalent stress and to verify if the strength and stiffness of the main girder of the portal crane meet the requirements. Secondly, multi-body dynamic simulation software Adams is adopted to construct a virtual prototype, to achieve the motion simulation of the crane working process and to output the loading spectrum in many working conditions. After that, fatigue analysis software - nCode Design-Life is applied to estimate the fatigue life of the portal crane. Finally, the crack propagation life of the portal crane is computed based on the theory of elastic fracture mechanics to verify whether the computing results of infinite elements model are correct.