Jinan City Research Articles

Numerical Simulation of Deformation and Failure of Drainage Boat Pond Caused by Underground Coal Mining-Induced Subsidence

The prediction of surface subsidence after underground coal mining is of practical significance for land planning and utilization in subsidence area. For a case study, the deformation and failure of a drainage boat pond caused by an underground coal mining-induced subsidence are investigated (the drainage boat pond is located in the Nanyang Lake Farm, Jining City, China). A mining subsidence prediction model suitable for the irregular coalface is established using the improved probability integral method to analyze the subsidence parameters. A numerical model of the boat pond deformation is established to simulate the stress, displacement, and plastic zone distribution of the boat pond. The boat pond deformation prevention structure is proposed from the prospects of pond bottom, pond slope, and pond slope protection. Moreover, the reinforcement of drainage boat pond is achieved in five steps. Finally, the deformation and failure state of the reinforcement boat pond under coal mining subsidence is simulated, and the rationality of the reinforcement measures is also verified by a field investigation. The research results have an important practical significance for water resource protection and structure construction in underground coal mining-induced subsidence.

중국 주택가격 형성요인에 관한 연구

Qingdao City is main city of Shandong Province along with Jinan City, one of Shandong Province's major cities. As the interest of the housing market is increasing, studies on Chinese real estate are also being actively conducted. However, the reserch on the housing price in Qingdao is relatively insufficient. The purpose of this study is to analyze the housing market in Qingdao and to analyze the formation factors for housing price in Qingdao. Hedonic price model was used as a model to analyze the housing price formation factors in Qingdao City, and data were collected from China's major housing trading site, Soupang Mang. The subjects of the study were six districts: Shinan, Shibei, Licang, Laoshan, Chengyang and Huangdao District. and the time range is for houses traded from 2014 to 2016. Housing characteristics affecting Qingdao housing prices are divided into regional characteristics, complex characteristics, household characteristics, and location characteristics. The main analysis results are as follows. First, in the regional characteristics, the prices of houses located in Shinan, Shibei, Licang, and Laoshan district were higher than those in other regions. Second, in the characteristics of the complex, the more the total number of households in the complex, the shorter the elapsed years, the more famous the contractor who built the house, the house has a higher price. Third, in the characteristics of the household, the larger the supply area, the higher the price when the household's scent is south or south. Lastly, in terms of location characteristics, it was found that the distance from the park or bus stop is short, or the prices of houses located close to the subway are high.

Research on the Temporal and Spatial Evolution of the Dynamic Coupling and Coordinated Development of Two-Way FDI in Jinan City

Under the background of "dual circulation", to implement the international investment concept of "bringing in" and "going global", it is urgent to realize the coupling and coordinated development of IFDI and OFDI. On the basis of trying to explore the coupling and coordination mechanism of two-way FDI in Jinan City, this paper uses the system coupling evaluation model to measure the coupling degree and coupling coordination degree. The results show that from 2003 to 2020, the coupling degree of two-way FDI in Jinan was at a high level of coupling, but the coupling coordination degree was low.

Authentic leadership and innovation behaviour among nurses in China: A mediation model of work engagement.

The purpose of this study was to explore the effect of authentic leadership on nurses' innovation behaviour and the mediating role of work engagement. Encouraging nurses to generate more innovation behaviours has become an important development direction for improving the quality of nursing services. We employed a self-report questionnaire to collect data in Jinan City, China. A total of 2018 valid surveys were obtained. Hierarchical multiple regression model analysis was conducted to test the study hypothesis. The mean values of authentic leadership were 55.72 and 35.29, respectively. It shows that nurses can perceive the authenticity of managers, and their innovation behaviours need to be improved. Work engagement was found to have partially mediating effect on the relationship between authentic leadership and innovation behaviour. Results suggest the importance of developing nurse managers' authentic leadership to foster nurses' work engagement and innovation behaviour. Hospitals should enhance authentic leadership by designing leadership training programmes and establishing authentic culture. In addition, nursing managers can also foster nursing innovation through improvements in work engagement. The study data were collected via questionnaires, and we sent out questionnaires with informed consent forms to the study subjects. All valid subjects signed the consent forms and agreed to join this study. In addition, the questionnaires were collected anonymously, and all the subjects' information is strictly confidential. More importantly, the data are only used for research and do not involve any commercial interests.

Risk Factors Affecting Cognitive Impairment of the Elderly Aged 65 and Over: A Cross-Sectional Study.

ObjectivesElderly population with cognitive impairment has been accelerating in China. This study aimed to explore the relationship between each risk factor and each cognitive domain to provide evidence for risk prevention of controlling impaired cognitive function in elderly.MethodsThis cross-sectional study analyzed the cognitive status of the elderly aged 65 and above in three communities in Shizhong District of Jinan City. Cognitive status was assessed by MMSE. The influencing factors of cognitive impairment were analyzed by chi square test, correlation analysis and regression analysis.ResultsAmong 1,171 participants, 643 were defined as cognitive impairment with an incidence of 54.9%. And we found that there were significant differences in the incidence of cognitive impairment among residents with different gender, age, education level, hypertension and LDL-C (P < 0.05). However, BMI, marital status, smoking, physical exercise, T2DM, TC, TG and HDL-C had no significant differences in the incidence of cognitive impairment. In addition, education level (b = 1.194, P <0.001), age (b = −0.040, P = 0.001), LDL-C (b = 0.169, P = 0.018) had statistical significance on the total score of MMSE according to binary logistic regression analysis.ConclusionGender, age, education level, hypertension and LDL-C had significant differences in the incidence of cognitive impairment. And these risk factors could provide a basis for the early screening and intervention of cognitive impairment in the elderly.

A novel PM2.5 concentrations probability density prediction model combines the least absolute shrinkage and selection operator with quantile regression.

PM2.5 has a significant negative impact on human health and atmospheric quality, and accurate prediction of its concentration is necessary. When using common point prediction models for PM2.5 concentration prediction, the influence of various uncertainties on PM2.5 concentrations makes the prediction results suffer from poor accuracy. To address this issue, this paper proposes the quantile regression neural network (QRNN) model based on the least absolute shrinkage and selection operator (LASSO), combined with kernel density estimation (KDE) for probabilistic density prediction of PM2.5 concentrations. The model uses LASSO regression to select the influential factors, and then the quartiles of daily PM2.5 concentrations calculated by the QRNN model are imported into the KDE model to obtain the probability density predictions of PM2.5 concentrations. In the paper, empirical analyses are carried out with the cities of Beijing and Jinan in China as well as six other datasets, and the prediction performance of the model is assessed by using evaluation criteria in both point prediction and interval prediction. The simulation reveals that the predictive performance of the LASSO-QRNN-KDE model is well, and the model is not only effective in filtering high-dimensional data, but also has a higher accuracy compared to common research models. In addition, the model is able to describe the uncertainty of PM2.5 concentration fluctuations and carry more information on the variation of PM2.5 concentrations, which can provide a novel and excellent PM2.5 concentration prediction tool for relevant policy makers.

AUTOMATIC IDENTIFICATION METHOD OF CONSTRUCTION AND DEMOLITION WASTE BASED ON DEEP LEARNING AND GAOFEN-2 DATA

Abstract. Due to the relatively complex construction and demolition waste (C&amp;amp;DW) spectrum and texture, it is difficult to identify C&amp;amp;DW by simply constructing a remote sensing index. Therefore, this study proposes an automatic identification method of C&amp;amp;DW based on deep learning and the Gaofen-2 (GF-2) Data. Pingdingshan City and Jining City in China were selected as the research areas in the study. The dataset used for deep learning training and testing in the study area was captured by the GF-2 Data. On the basis of this dataset, the deep learning model DeepLabv3+ is used to identify C&amp;amp;DW. The overall accuracy rate of the deep learning model for identifying C&amp;amp;DW is 82.02%, and the overall mIoU is 82.39%. The accuracy of the model for the identification of C&amp;amp;DW areas is further verified by ground verification. The results of this study are helpful for the survey and management of C&amp;amp;DW, which is beneficial to the study of spatial and temporal distribution of urban C&amp;amp;DW, resource utilization and environmental pollution risk reduction.

Chemical characterization, source apportionment, and health risk assessment of PM2.5 in a typical industrial region in North China.

To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 ± 43.9μg·m-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO3- ion, at 14.6 ± 14.2μg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8μg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9μg·m-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2ng·m-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.

Observational studies: Ambient air pollution and hospitalization for RA-ILD in a heavily polluted city in China.

Little is known within the medical community about the impact of air pollution on hospital admissions due to rheumatoid arthritis associated with interstitial lung disease (RA-ILD). Our research aimed to explore whether there is a correlation and to estimate how the association was distributed across various lags in Jinan, China.The relationships between ambient air pollutant concentrations, including PM2.5, PM10, sulfur dioxide (SO2), ozone (O3), and nitrogen dioxide (NO2), and monthly hospitalizations for RA-ILD were studied by employing a general linear model with a Poisson distribution. This time-series study was performed from January 1st, 2015 to December 31st, 2019.In the 5-year study, there were 221 hospitalizations for RA-ILD in Jinan city. The levels of PM2.5, PM10, SO2, and NO2 were significantly related to the number of admissions for RA-ILD. PM2.5, PM10, and SO2 showed the most significant effect on the month (lag 0), and NO2 was most related to RA-ILD at a lag of two months (lag 2). The monthly admissions of RA-ILD increased by 0.875% (95% CI: 0.375–1.377%), 0.548% (95% CI: 0.148–0.949%), 1.968% (95% CI: 0.869–3.080%), and 1.534% (95% CI: 0.305–2.778%) for each 10 μg/m3 increase in PM2.5, PM10, SO2 and NO2, respectively.This study might add more detailed evidence that higher levels of PM2.5, PM10, SO2 and NO2 increase the risk of hospitalizations for RA-ILD. Further study of the role of air pollution in the pathogenesis of RA-ILD is warranted.

First Report of Fruit Rot Caused by Fusarium luffae in Muskmelon in China.

Muskmelon(Cucumis meloL.) is one of the most widely cultivated and economically important fruit crops in the world.However, many pathogens can cause decay ofmuskmelon fruit, including Fusarium spp.. Fusarium spp. are the most important pathogen, affecting muskmelon fruit yield and quality (Wang et al. 2011). In August 2020, fruitrot symptoms were observed on ripening muskmelons (cv. Tianbao) in several fields in Jiyang District, Jinan City of Shandong Province, China. The incidences of infected muskmelon ranged from 15% to 30% and caused an average 20% yield loss. Symptoms appeared as pale brown, water-soaked lesions that were irregular in shape, with the lesion sizes ranging from a small spot (1 to 2 cm) to decay of the entire fruit. The core and surface of infected fruit were colonized and covered with white mycelia. Two infected muskmelons were collected from two fields, 3.5 km apart. Tissues removed from inside the infected fruit were surface disinfected with 75% ethanol for 30 s, and cultured on potato dextrose agar (PDA) at 25°C in the dark for 5 days. Four purified cultures were obtained using the single spore method.On carnation leaf agar (CLA), 3 to 5 septate, falcate, with a pronounced dorsiventral curvature macroconidia with tapered apical cell, and foot-shaped basal cell, measuring 20 to 40 × 3.5 to 4.5 μm. Microconidia and chlamydospores were not observed. These morphological characteristics were consistent with the description of F. luffae (Wang et al., 2019). Because these isolates had similar morphology, two representative isolates (XP11 and XP12) were selected for multilocus phylogenetic analyses. DNA was extracted from the representative isolates using a CTAB method. Nucleotide sequences of the internal transcribed spacers (ITS) (White et al. 1990), calmodulin (CAM), RNA polymerase II second largest subunit (RPB2), translation elongation factor 1-α gene (TEF1) (Xia et al. 2019) were amplified using specific primers, sequenced, and deposited in GenBank (ITS: MW391509 and MW391510, CAM: MW392789 and MW392790, RPB2: MW392797 and MW392798, TEF1: MW392793 and MW392794). Alignments of a combined dataset of ITS, CAM, RPB2 and TEF1 were made using MAFFT v. 7, and phylogenetic analyses were conducted in MEGA v. 7.0 using the maximum likelihood method. The muskmelon isolates (XP11 and XP12) clustered together with theF. luffae reference strain LC12167 (99% bootstrap). To perform a pathogenicity test, 10 μl of conidial suspensions (1 × 106 conidia/ml) were injected into each muskmelon fruit using a syringe, and the control fruit was inoculated with 10 μl of sterile distilled water. There were ten replicated fruits for each treatment. The test was repeated three times. After 7 days at 25°C, the interior of the inoculated muskmelons begun to rot, and the rot lesion expanded from the core towards the surface of the fruit, then white mycelia were produced on the surface. Ten isolations were re-isolated from the infected tissues and confirmed to fulfill Koch's postulates. No symptoms were observed on the control muskmelons. To our knowledge, this is the first report of fruit rot caused by F. luffae in muskmelon in China. Considering the economic value of the muskmelon crop, correct identification can help farmers select appropriate field management measures for control of this disease.

Analysis of the Correlation between Academic Performance and Learning Motivation in English Course under a Corpus-Data-Driven Blended Teaching Model

To explore the correlation between academic performance and learning motivation in English course under a corpus-data-driven blended teaching model, this study set research objects as 62 year-2020-enrolled undergraduate students majoring in English from a university in Jinan City, Shandong Province, eastern China. According to their previous frequencies of using information technology to learn English, these 62 students were divided into two groups: practice group with high frequency and control group with low frequency, with 31 students in each group. The two groups of students were taught 3 English lessons per week for a total of 15 weeks by the exact same teachers using a corpus-data-driven blended teaching model. The students’ English academic performances were assessed by well-organized final tests, and their English learning motivations were measured by a motivation scale and questionnaires. The results show that the correlation coefficients between the average score of motivation questionnaires, intrinsic motivation factors, extrinsic motivation factors, and the average score of academic performances in practice group were 0.894, 0.682, and 0.724, respectively, while those in control group were 0.749, 0.836, and 0.904. In all the above correlation analyses, the significance level is 0.01, and all coefficient values are higher than critical value. Hence, there is a positive correlation between learning motivation and academic performance of the two groups of subjects. It is found that the corpus-data-driven blended teaching model has a significant impact on college students’ English academic performance and learning motivation, and it has a positive effect on the improvement of their English academic performance and the cultivation of learning motivation. In general, the key to this teaching model lies in reasoning and acquisition by analyzing the language provided by the corpus, and the whole process of data-driven learning is student-centered. Students are exposed to a large number of authentic language knowledge and cultural information, which promotes the sensitivity to relevant points. The results of this paper provide a reference for further research on the analysis of the correlation between academic performance and learning motivation in English course under the corpus-data-driven blended teaching model.

Construction of Green Space Ecological Network in Jinan City Based on MSPA and MCR Model

Construction of Green Space Ecological Network in Jinan City Based on MSPA and MCR Model

Changes in Soil Ectomycorrhizal Fungi Community in Oak Forests along the Urban–Rural Gradient

The ectomycorrhizal fungi communities of forests are closely correlated with forest health and ecosystem functions. To investigate the structure and composition of ectomycorrhizal fungi communities in oak forest soil and their driving factors along the urban–rural gradient, we set up a Quercus acutissima forest transect and collected samples from the center to the edge of Jinan city (urban, suburban, rural). The results showed that the ectomycorrhizal fungal community composition at the phyla level mainly included Basidiomycota and Ascomycota in three sites. At the genus level, the community compositions of ectomycorrhizal fungi, along the urban–rural gradient, exhibited significant differences. Inocybe, Russula, Scleroderma, Tomentella, Amanita and Tuber were the dominant genera in these Quercus acutissima forests. Additionally, the diversity of ectomycorrhizal fungi was the highest in rural Quercus acutissima forest, followed by urban and suburban areas. Key ectomycorrhizal fungi species, such as Tuber, Russula and Sordariales, were identified among three forests. We also found that pH, soil organic matter and ammonium nitrogen were the main driving factors of the differences in ectomycorrhizal fungi community composition and diversity along the urban–rural gradient. Overall, the differences in composition and diversity in urban–rural gradient forest were driven by the differences in soil physicochemical properties resulting from the forest location.

The effect and its critical window for ambient temperature and humidity in pregnancy on term low birth weight.

As common meteorological factors in daily life, there is limited evidence for the effect of ambient temperature and humidity during pregnancy on the risk of term low birth weight. Furthermore, little is known about the interaction of ambient temperature and humidity on TLBW. The objective of the study was to explore the effect of ambient temperature, humidity during pregnancy, and their interaction on the risk of TLBW and, moreover, to identify exposure critical window. We recruited 6640 infants and their mothers to build a birth cohort study in Jinan City, China, from January 2018 to December 2019. The associations between temperature and humidity during pregnancy and TLBW were estimated by generalized additive model, logistic regression model, and interaction analysis, and the critical window was identified by the distributed lag non-linear model. The incidence of TLBW was 1.36% for the infants in the birth cohort. TLBW was related to the low level of temperature and humidity in the whole pregnancy, compared with the moderate level and the adjusted ORs were 4.44 (1.65-11.42) and 6.23 (1.92-21.39), respectively. The indicators of the interaction analysis of temperature and humidity were not statistically significant. For the low level of humidity, the association with TLBW was statistically significant at first to sixth gestational weeks, and the maximum OR in male infants (3.95, 1.70-9.16) was higher than that in females (1.96, 1.06-3.63). For the low level of temperature, we failed to find significant association with TLBW at each gestational week. The low level of temperature and humidity during pregnancy could increase the risk of TLBW. There was no statistical interaction between temperature and humidity on TLBW. Moreover, the early stage of pregnancy was the critical window for humidity exposure, in which the boys had a greater effect.

A Multiobjective Fractional Programming for a CHP System Operation Optimization Based on Energy Intensity

The objective of this research is to establish a multiobjective fractional programming (MOFP) model for supporting the operational management of a combined heat and power (CHP) system. Compared with the traditional operational optimization model of the CHP system, the importance of the energy intensity (i.e., the ratio of energy consumption and energy production) was emphasized in the MOFP model, which is considered as the system objective for replacing the common objective of minimizing the economic cost. This innovative transformation effectively reduces excessive energy consumption, accompanied by improvement in the system revenue. The CHP system of an industrial park in the City of Jinan, China, was used as a study case for demonstration. The obtained results reflected that the combination of two gas turbines (GTs) ensured safe, efficient, and stable output for meeting daily power requirements in various seasons. As for the steam load, during the summer, two heat recovery steam generators (HRSGs) play a major role, where the insufficient part is supplemented by two gas-fired boilers (SBs); conversely, the steam load in winter is mainly satisfied by the aid of two SBs. The successful application of the MOFP model in the park could provide a good demonstration for CHP management in many other districts and cities.

Temporal and Spatial Variation in O3 Concentration Near the Surface of Shandong Peninsula and Analysis of Potential Source Areas

The purpose of this study was to explore the temporal and spatial distribution characteristics and potential sources of ozone (O3) in the Shandong Peninsula over a long period of time based on the analysis of the temporal and spatial changes in O3 concentration in Shandong Peninsula from 2005 to 2020. We used wavelet analysis, the entropy weight method, and correlation analysis to discuss O3 and its influencing factors and researched the potential sources of O3 in Shandong Peninsula. The results showed that:① in terms of the time pattern, the near-surface O3 in Shandong Peninsula showed a "triple peak" trend from 2005 to 2020, reaching the maximum value of[(40.48±7.64) μg·m-3] in 2010 and a minimum value of[(36.63±5.61) μg·m-3] in 2013. The season was expressed as:summer[(42.49±1.7) μg·m-3]>spring[(40.65±0.6) μg·m-3]>autumn[(36.47±0.7) μg·m-3]>winter[(36.46±0.3) μg·m-3]. ② In terms of the spatial pattern, the O3 concentration of Shandong Peninsula gradually increased with the increase in latitude from 2005 to 2020, showing the characteristics of high concentrations in the east and west and low in the middle region. During the 16-year evolution of the O3 concentration, there was a 1.5 a main oscillation period. ③The analysis of meteorological conditions revealed that O3 concentration was positively correlated with temperature, precipitation, relative humidity, and sunshine hours, whereas pressure and wind speed were negatively correlated. In the analysis of social factors, soot (dust) emissions were the most obvious factor affecting the third indicator, with a weight of 0.25. ④ Through simulating the trajectory of airflow from different regions (Ji'nan and Qingdao), it was found that the ocean airflow contributed 10.69% to Jinan and 48.94% to Qingdao. There was 64.04% of the long-distance air mass transmission path coming from the northwest, and 43.69% of the short-distance air mass transmission path was from the Bohai Sea and the Yellow Sea, followed by Shandong Province with 21.01%. ⑤ The analysis of potential sources of O3 showed that the potential sources of Ji'nan were mainly distributed in Jinzhou, Liaoning Province, northern Jiangsu Province, Hubei Province, and Anhui Province, with a WPSCF value >0.6, and Qingdao's WPSCF value of >0.6 was mainly distributed in the Yellow Sea area. The O3 contribution of Jining City, Linyi City, Xuzhou City, Huaibei City, and Lianyungang City was >40 μg·m-3. The area with >45 μg·m-3 in Qingdao was mainly in the Yellow Sea. Through the analysis of potential sources in the Shandong Peninsula, particular attention should be paid to the supply of industrial sources in the surrounding areas and the marine sources provided by marine air pollution.

Study of incidence and economic burden of herpes zoster based on community investigation among the aged in Laiwu district, Jinan city, Shandong Province of China

Objective: To understand the incidence and economic burden of herpes zoster among the aged in Laiwu district, Jinan city. Methods: Retrospective cohort study was conducted in 5 communities in Laiwu District, Jinan City from July to September, 2019. A total of 8 300 residents born before July 1, 1959 and aged ≥60 years old were included in the investigation. At the same time, an economic burden survey was carried out among 220 cases who developed herpes zoster after July 1, 2017. A questionnaire was used to collect information on incidence and economic burden of HZ, and comparisons were carried out about the incidence and economic burden of herpes zoster among older people with different characteristics. Results: The age of 8 300 subjects was (71.46±6.71) years old. Male and female accounted for 44.10% and 55.90%, respectively. The cumulative incidence of disease after the age of 60 was 73.61‰ among population aged ≥60 years old. The cumulative incidence was 28.03‰, 71.26‰, 86.09‰, 93.48‰ and 88.10‰ among population aged 60-64, 65-69, 70-74, 75-79 and ≥80 years old,respectively. The average annual incidence of HZ was 9.49‰ and annual incidence was 7.59‰, 7.23‰, 8.43‰, 10.24‰ and 13.98‰ in 2014-2018, respectively. HZ cost was (2 626±667) RMB per patient with a median cost of 715 RMB (interquartile range 303-2 358) on 220 cases who developed disease after July 1, 2017. The cost of outpatient cases was (1 329±1 835) RMB per patient with a median cost of 560 RMB (interquartile range 300-1 320), and the cost of inpatient cases was (14 303±16 571) RMB per patient with a median cost of 8 190 RMB (interquartile range 4 368-15 160). Conclusion: The incidence of HZ is high among population aged≥60 years old, which could cause heavy economic burden for them.

Research on the Association of Consumption Structure With Industrial Structure and Economic Growth in Jinan City

This paper empirically investigates the relationship between consumption structure, industrial structure and economic growth in Jinan City using vector autoregressive (VAR) model using 30 years of data from 1990-2020 in Jinan City. The results show that there is a two-way causal relationship between industrial structure and economic growth, and a two-way causal relationship between consumption structure and economic growth in Jinan City. Consumption structure can promote the optimization of industrial structure and further promote economic growth, while industrial structure does not play a proper role in promoting the regulation of consumption structure.

Numerical Simulation of the Effect of Construction Dust Emission on Air Quality in Jinan, a Central City in the North China Plain

&lt;p&gt;Numerical simulation was conducted to assess the impact of dust emission on typical environmental sites in Jinan City. The CALPUFF model was applied to five simulation scenarios. The results showed that dust emission had a significant impact on air quality in Jinan. The impact of dust emission on the average concentration of PM10 at 15 monitoring sites was 19.8 μg/m3, accounting for 14.9% of the annual total. The impact of dust emission on the average concentration of PM2.5 was 5.2 μg/m3, accounting for 8.1% of the annual total. Adoption of yellow warning measures in the emission reduction scenarios had insignificant environmental effects due to unfavorable meteorological conditions. Compared with the baseline scenario, the average concentrations of PM10 and PM2.5 decreased by 13.6% and 1.9%, respectively. After adoption of orange and red warning measures, the impact of site dust emission on air quality at the monitoring site was reduced significantly. Significant environmental effects were achieved after all construction sites within a 2-km radius of the monitoring site were closed. Compared with the baseline scenario, the average concentrations of PM10 and PM2.5 were reduced by 45.5% and 42.3%, respectively. The results showed that under adverse meteorological conditions, higher-level warning measures should be undertaken to reduce the impact of site emissions on environmental quality. Considering the economic and social effects of emission reduction, temporary construction stoppage within 2 km of the monitoring site is a feasible plan that is in accordance with the goals of comprehensive environmental management.&lt;/p&gt;&#x0D;

Empirical study on comparative analysis of dynamic degree differences of land use based on the optimization model

The land use dynamic degree model is constantly improved with the in-depth development of land use change research to optimize research results. On the basis of the analysis and summary of existing land use dynamic degree models, this study proposes an optimization model. We take the analysis of land use change in Jining City as an example for empirical research. Results show that the simulation effect of the optimized land use dynamic degree model is more reliable. The optimized single land use dynamic degree model can more truly reflect the intensity of changes in various land use types. The optimized comprehensive land use dynamic degree model can better reflect the intensity of regional land use changes; thus, hot spots of land use changes are easier to identify.