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China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province. [ABSTRACT FROM AUTHOR]

Background: In November 2015, China launched a pilot program for its Drug Marketing Authorization Holder (MAH) system, aiming to integrate production and research and development resources to spur drug innovation. While many scholars have examined the theoretical relationship between the MAH system and pharmaceutical manufacturing innovation, empirical studies have been scarce. Methods: This study uses inter-provincial panel data on China's pharmaceutical manufacturing industry from 2009 to 2019, along with synthetic control methods, to offer a robust analysis of the impact of the MAH paradigm on innovation quality in pilot provinces. We treat the 2015 MAH system implementation in ten provinces as a natural experiment and account for the mediating effects of R&D investments, allowing us to discern the underlying mechanisms. Results: Our findings demonstrate a significant positive effect of China's MAH system on innovation quality in the pharmaceutical manufacturing industry. Specifically, the system is most effective in Jiangsu, Guangdong, and Shandong provinces. We also identify R&D investments as playing a mediating role in facilitating the favorable impact of the MAH system on innovation quality. Conclusion: Our study highlights the crucial importance of the MAH system in promoting innovation quality in China's pharmaceutical manufacturing industry, providing vital empirical support for its adoption and further enhancement. This research also offers practical insights for policymakers and R&D decision-makers in the pharmaceutical sector. [ABSTRACT FROM AUTHOR]

Background: Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infectious diseases incidence is of great significance for public health organizations to prevent the spread of diseases. However, only using historical incidence data for prediction can not get good results. This study analyzes the influence of meteorological factors on the incidence of hepatitis E, which are used to improve the accuracy of incidence prediction. Methods: We extracted the monthly meteorological data, incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We employ GRA method to analyze the correlation between the incidence and meteorological factors. With these meteorological factors, we achieve a variety of methods for incidence of hepatitis E by LSTM and attention-based LSTM. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results: Duration of sunshine and rainfall-related factors(total rainfall, maximum daily rainfall) are more relevant to the incidence of hepatitis E than other factors. Without meteorological factors, we obtained 20.74%, 19.50% for incidence in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we obtained 14.74%, 12.91%, 13.21%, 16.83% for incidence, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.83%. Without meteorological factors, we achieved 20.41%, 19.39% for cases in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we achieved 14.20%, 12.49%, 12.72%, 15.73% for cases, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.92%. More detailed results are shown in results section of this paper. Conclusions: The experiments show that attention-based LSTM is superior to other comparative models. Multivariate attention and temporal attention can greatly improve the prediction performance of the models. Among them, when all meteorological factors are used, multivariate attention performance is better. This study can provide reference for the prediction of other infectious diseases. [ABSTRACT FROM AUTHOR]

Improving culture and tourism integration efficiency is an important way to promote the high-quality development of cultural tourism. According to the inherent requirements of high-quality development, this paper constructed an evaluation indicator system for culture and tourism integration efficiency. Then, the culture and tourism integration efficiency of 16 cities in Shandong Province, China during the period from 2010 to 2019 was measured with the benevolent DEA cross-efficiency model. On the basis of exploratory spatial data analysis and dynamic spatial Durbin model, we explored the spatio-temporal evolution characteristics and influencing factors of culture and tourism integration efficiency in Shandong Province. The results show that from 2010 to 2019, the culture and tourism integration efficiency in Shandong Province has experienced three stages of "rapid growth-rapid decline-stable rise period". The spatial pattern has changed from "high in the east and low in the west" to "high in the central and low in the north and south", and regions with high integration efficiency are mainly concentrated in Jiaodong Peninsula. The level of economic development significantly promotes the culture and tourism integration efficiency in local and neighboring cities in the short and long term, while policy environment has a significant negative impact. Traffic conditions and human capital only promote the culture and tourism integration efficiency in local cities. The level of information development and openness degree only have a long-term effect on the culture and tourism integration efficiency, without short-term effect. The research results are of great significance to improve the growth quality and sustainable development of cultural tourism in Shandong Province. Our work could provide a scientific basis for maximizing the allocation benefits of cultural and tourism resources in similar regions in the world. [ABSTRACT FROM AUTHOR]

Background: Accurate and reliable predictions of infectious disease can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task. However, for different data series, the performance of these models varies. Hepatitis E, as an acute liver disease, has been a major public health problem. Which model is more appropriate for predicting the incidence of hepatitis E? In this paper, three different methods are used and the performance of the three methods is compared. Methods: Autoregressive integrated moving average(ARIMA), support vector machine(SVM) and long short-term memory(LSTM) recurrent neural network were adopted and compared. ARIMA was implemented by python with the help of statsmodels. SVM was accomplished by matlab with libSVM library. LSTM was designed by ourselves with Keras, a deep learning library. To tackle the problem of overfitting caused by limited training samples, we adopted dropout and regularization strategies in our LSTM model. Experimental data were obtained from the monthly incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results: By analyzing data, we took ARIMA(1, 1, 1), ARIMA(3, 1, 2) as monthly incidence prediction model and cases number prediction model, respectively. Cross-validation and grid search were used to optimize parameters of SVM. Penalty coefficient C and kernel function parameter g were set 8, 0.125 for incidence prediction, and 22, 0.01 for cases number prediction. LSTM has 4 nodes. Dropout and L2 regularization parameters were set 0.15, 0.001, respectively. By the metrics of RMSE, we obtained 0.022, 0.0204, 0.01 for incidence prediction, using ARIMA, SVM and LSTM. And we obtained 22.25, 20.0368, 11.75 for cases number prediction, using three models. For MAPE metrics, the results were 23.5%, 21.7%, 15.08%, and 23.6%, 21.44%, 13.6%, for incidence prediction and cases number prediction, respectively. For MAE metrics, the results were 0.018, 0.0167, 0.011 and 18.003, 16.5815, 9.984, for incidence prediction and cases number prediction, respectively. Conclusions: Comparing ARIMA, SVM and LSTM, we found that nonlinear models(SVM, LSTM) outperform linear models(ARIMA). LSTM obtained the best performance in all three metrics of RSME, MAPE, MAE. Hence, LSTM is the most suitable for predicting hepatitis E monthly incidence and cases number. [ABSTRACT FROM AUTHOR]

The green development of coastal urban agglomerations, which are strategic core areas of national economic growth in China, has become a major focus of both academics and government agencies. In this paper, China's coastal urban agglomeration is taken as the research area, aiming at the serious air pollution problem of coastal urban agglomeration, geographic information system (ArcGIS10.2) spatial analysis and the spatial Dubin model were applied to National Aeronautics and Space Administration atmospheric remote sensing image inversion fine particulate matter (PM2.5) data from 2010–2016 to reveal the temporal and spatial evolution characteristics and Influence mechanism of PM2.5 in China's coastal urban agglomerations, with a view to providing a reference value for coordinating air pollution in the coastal cities of the world. From 2010–2016, the PM2.5 concentration in China's coastal urban agglomerations decreased as a whole, and large spatial differences in PM2.5 concentration were observed in China's coastal urban agglomerations; the core high-pollution areas were the Beijing–Tianjin–Hebei, Shandong Peninsula, and Yangtze River Delta urban agglomerations. Large spatial differences in PM2.5 concentration were also observed within individual urban agglomerations, with higher PM2.5 concentrations found in the northern parts of the urban agglomerations. Significant spatial autocorrelation and spatial heterogeneity were observed among PM2.5-polluted cities in China's coastal urban agglomerations. The northern coastal urban agglomerations formed a relatively stable and continuous high-pollution zone. The spatial Dubin model was used to analyze the driving factors of PM2.5 pollution in coastal urban agglomerations. Together, meteorological, socioeconomic, pollution source, and ecological factors affected the spatial characteristics of PM2.5 pollution during the study period, and the overall effect was a mixed effect with significant spatial variation. Among them, meteorological factors were the greatest driver of PM2.5 pollution. In the short term, the rapid increase in population density, industrial emissions, industrial energy consumption, and total traffic emissions were the important driving factors of PM2.5 pollution in the coastal urban agglomerations of China. [ABSTRACT FROM AUTHOR]

Complexity modelling of economic efficiency and growth potential is increasingly essential for countries and provinces. Evaluating the monetary flows, kinetic energy (efficiency) and potential capacity (resilience) provides crucial information for economic development. In the paper, the authors analyze growth opportunities for the Chinese economy from a system science point of view, using the perspective of information entropy, based on the input-output tables. Over the past four decades of reform and opening-up, China has made remarkable progress in its economic development. In 2007, China's GDP was at its fastest pace in history at 14.2% growth. However, after the financial crisis in 2008, the global economy experienced a downward trend and China's economic development also settled on a medium-low level of development. The traditional perspective is to rank regional development only based on GDP growth, whereas here, the authors advocate another evaluation method based on efficiency and potential growth. Unbalanced regional economic development has become problematic and has become a barrier for sustainability of China's economy. The results of the research indicate firstly that China's regional development in 2007 and 2012 has been unequal between the provinces. Secondly, the authors found that Shandong province had significantly higher indicators for efficiency and potential growth than others in the same circumstances. Authors observe that provinces tend to carry out industrial policies and adjust the structure of industry on a local level. This analysis demonstrates that the spatial imbalance of efficiency and potential of economic development under the perspective of provincial-level regions. From the perspective of industry, it indicates that the supply chain is too short, mainly focusing on the mining and processing of resources and minerals in the original upstream industry chain, while the downstream is not fully utilized. These represent some unique insights yielded through this type of analysis that authors advocate applying more broadly. [ABSTRACT FROM AUTHOR]

Water and land resource utilization is an important driving force of changes in ecosystem services; therefore, research on multi-parameter coupling systems that consider "ecosystem services, water resources, and land resources" together has key significance for river basins. This study aims to reveal the interaction and mutual influence of ecosystem services and water and land resources in the Daguhe River Basin, China, based on the coupling coordination degree model. The results showed that during the period from 2000 to 2010, the coupling coordination degree values for the years 2000, 2005, and 2010 were 0.6005, 0.7292, and 0.8037. The corresponding coupling coordination classifications were categorized as "primary coordinated development", "intermediate coordinated development," and "well-coordinated development", respectively. These results reflected the fact that the relationship between water and land resource utilization and the environment tends to evolve in the direction of coordinated development (an improvement in one part corresponds to an improvement in another part) with variation in water and land utilization types, and eventually pushes the whole resource, as well as ecological and environmental systems, from low to high levels of coupling coordination degrees as observed in case of the Daguhe River Basin, China. Our research provides an overview of the interaction between ecosystem services and water and land resources in the Daguhe Basin and even in the Shandong Province. With our results, we offer new perspectives on river basin management and for planning future eco-environmental policies (the policy is specifically designed for the ecological environment) by combining water and land resource utilization. [ABSTRACT FROM AUTHOR]

With the continuous development of the world economy, science, and technology, the era of intelligence and information is upon us. Through the implementation of the digital rural construction project in China, agriculture is developing rapidly in the direction of informatization. As a major agricultural province in China, Shandong Province has been ranked first in China for many years in terms of gross agricultural product and the import and export of agricultural products. According to the current situation of agricultural informatization in Shandong Province, this study uses relevant evaluation index data of Shandong Province from 2011 to 2019 and applies the entropy value method, coupling degree analysis model, and coupling coordination degree analysis model to deeply evaluate the mutual influence and coordination degree between the agricultural informatization level and agricultural economic development in Shandong province in each year. We identify the possible problems in the development of agricultural informatization in Shandong province. Finally, in terms of talent construction, infrastructure construction, the main role of government, policies, and farmers' awareness of informatization, we propose some countermeasures and suggestions that are conducive to the coordinated development of agricultural informatization and the agricultural economy. [ABSTRACT FROM AUTHOR]

Due to the rapid economic growth and the heavy reliance on fossil fuels, China has become one of the countries with the highest sulfur dioxide (SO2) emissions, which pose a severe challenge to human health and the sustainable development of social economy. In order to cope with the serious problem of SO2 pollution, this study attempts to explore the spatial temporal variations of industrial SO2 emissions in China utilizing the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data. We first explored the relationship between the NSL data and the statistical industrial SO2 emissions at the provincial level, and confirmed that there was a positive correlation between these two datasets. Consequently, 17 linear regression models were established based on the NSL data and the provincial statistical emissions to model the spatial-temporal dynamics of China's industrial SO2 emissions from 1997 to 2013. Next, the NSL-based estimated results were evaluated utilizing the prefectural statistical industrial SO2 emissions and emission inventory data, respectively. Finally, the distribution of China's industrial SO2 emissions at 1 km spatial resolution were estimated, and the temporal and spatial dynamics were explored from multiple scales (national scale, regional scale and scale of urban agglomeration). The results show that: (1) The NSL data can be successfully applied to estimate the dynamic changes of China's industrial SO2 emissions. The coefficient of determination (R2) values of the NSL-based estimation results in most years were greater than 0.6, and the relative error (RE) values were less than 10%, when validated by the prefectural statistical SO2 emissions. Moreover, compared with the inventory emissions, the adjusted coefficient of determination (Adj.R-Square) reached 0.61, with the significance at the 0.001 level. (2) During the observation period, the temporal and spatial dynamics of industrial SO2 emissions varied greatly in different regions. The high growth type was largely distributed in China's Western region, Central region, and Shandong Peninsula, while the no-obvious-growth type was concentrated in Western region, Beijing-Tianjin-Tangshan and Middle south of Liaoning. The high grade of industrial SO2 emissions was mostly concentrated in China's Eastern region, Western region, Shanghai-Nanjing-Hangzhou and Shandong Peninsula, while the low grade mainly concentrated in China's Western region, Middle south of Liaoning and Beijing-Tianjin-Tangshan. These results of our research can not only enhance the understanding of the spatial-temporal dynamics of industrial SO2 emissions in China, but also offer some scientific references for formulating feasible industrial SO2 emission reduction policies. [ABSTRACT FROM AUTHOR]

Considering the serious land-based pollution and the weak water exchange ability of western Laizhou Bay, it is essential to conduct an ecological risk assessment of the pollutants in this area. In this study, the ecological risk caused by heavy metals deposited in the surface sediments and those resuspended in the seawater of western Laizhou Bay was evaluated using probabilistic approaches. First, the concentrations of seven heavy metals, namely As, Cd, Cr, Cu, Hg, Pb, and Zn, in the surface sediments and seawater of western Laizhou Bay were detected during the spring and autumn of 2016. The concentrations of As, Cd, Cr, Cu, and Pb were found to be at levels comparable to those in the other global coastal systems, while those of Hg and Zn were lower than those in other coastal areas. Next, an ecological risk assessment of heavy metals in the surface sediments was performed using a typical potential ecological risk index and refined by using a Monte Carlo simulation. The results suggested low risk for the heavy metals detected in the sediments of western Laizhou Bay, with the exception of Hg in September 2016, which showed a probability (0.03%) of moderate risk. Meanwhile, the aquatic ecological risk assessment of the heavy metals was performed by applying a combination of hazard quotient (HQ) and joint probability curve. While the ecological risk of Cd, Hg, and Pb was found to be acceptable, the HQs for Cr, Cu, and Zn were greater than 1, and the overall risk probability of their adverse effects was higher than 0.05, suggesting certain ecological risk. Specifically, in the case of As, the overall risk probability was lower than 0.05, suggesting that its ecological risk was acceptable, although its HQ was greater than 1. Thus, by applying the probabilistic approaches, the ecological risk of the heavy metals in western Laizhou Bay was better characterized in this study, avoiding both overestimation and underestimation of ecological risk. [ABSTRACT FROM AUTHOR]

Antibiotic resistance is considered a major threat to global health and is affected by many factors, of which antibiotic use is probably one of the more important. Other factors include hygiene, crowding and travel. The rapid resistance spread in Gram-negative bacteria, in particular extended-spectrum beta-lactamase (ESBL) producing Enterobacteriaceae (ESBL-E), is a global challenge, leading to increased mortality, morbidity and health systems costs worldwide. Knowledge about resistance in commensal flora is limited, including in China. Our aim was to establish the faecal carriage rates of ESBL-E and find its association with known and suspected risk factors in rural residents of all ages in three socio-economically different counties in the Shandong Province, China. Faecal samples and risk-factor information (questionnaire) were collected in 2012. ESBL-E carriage was screened using ChromID ESBL agar. Risk factors were analysed using standard statistical methods. Data from 1000 individuals from three counties and in total 18 villages showed a high and varying level of ESBL-E carriage. Overall, 42% were ESBL-E carriers. At county level the carriage rates were 49%, 45% and 31%, respectively, and when comparing individual villages (n = 18) the rate varied from 22% to 64%. The high level of ESBL-E carriage among rural residents in China is an indication of an exploding global challenge in the years to come as resistance spreads among bacteria and travels around the world with the movement of people and freight. A high carriage rate of ESBL-E increases the risk of infection with multi-resistant bacteria, and thus the need for usage of last resort antibiotics, such as carbapenems and colistin, in the treatment of common infections. [ABSTRACT FROM AUTHOR]

Purpose: To examine the prevalence of refractive errors and prevalence and causes of vision loss among preschool and school children in East China. Methods: Using a random cluster sampling in a cross-sectional school-based study design, children with an age of 4–18 years were selected from kindergartens, primary schools, and junior and senior high schools in the rural Guanxian County and the city of Weihai. All children underwent a complete ocular examination including measurement of uncorrected (UCVA) and best corrected visual acuity (BCVA) and auto-refractometry under cycloplegia. Myopia was defined as refractive error of ≤−0.5 diopters (D), high myopia as ≤−6.0D, and amblyopia as BCVA ≤20/32 without any obvious reason for vision reduction and with strabismus or refractive errors as potential reasons. Results: Out of 6364 eligible children, 6026 (94.7%) children participated. Prevalence of myopia (overall: 36.9±0.6%;95% confidence interval (CI):36.0,38.0) increased (P<0.001) from 1.7±1.2% (95%CI:0.0,4.0) in the 4-years olds to 84.6±3.2% (95%CI:78.0,91.0) in 17-years olds. Myopia was associated with older age (OR:1.56;95%CI:1.52,1.60;P<0.001), female gender (OR:1.22;95%CI:1.08,1.39;P = 0.002) and urban region (OR:2.88;95%CI:2.53,3.29;P<0.001). Prevalence of high myopia (2.0±0.2%) increased from 0.7±0.3% (95%CI:0.1,1.3) in 10-years olds to 13.9±3.0 (95%CI:7.8,19.9) in 17-years olds. It was associated with older age (OR:1.50;95%CI:1.41,1.60;P<0.001) and urban region (OR:3.11;95%CI:2.08,4.66);P<0.001). Astigmatism (≥0.75D) (36.3±0.6%;95%CI:35.0,38.0) was associated with older age (P<0.001;OR:1.06;95%CI:1.04,1.09), more myopic refractive error (P<0.001;OR:0.94;95%CI:0.91,0.97) and urban region (P<0.001;OR:1.47;95%CI:1.31,1.64). BCVA was ≤20/40 in the better eye in 19 (0.32%) children. UCVA ≤20/40 in at least one eye was found in 2046 (34.05%) children, with undercorrected refractive error as cause in 1975 (32.9%) children. Amblyopia (BCVA ≤20/32) was detected in 44 (0.7%) children (11 children with bilateral amblyopia). Conclusions: In coastal East China, about 14% of the 17-years olds were highly myopic, and 80% were myopic. Prevalence of myopia increased with older age, female gender and urban region. About 0.7% of pre-school children and school children were amblyopic. [ABSTRACT FROM AUTHOR]

Background: Since 1997, several countries within the Asian Pacific region have been affected by one or more massive outbreaks of Hand Foot and Mouth Disease (HFMD). Virus typing experiments revealed that these outbreaks were caused by strains of human enterovirus 71 (EV71) belonging to several different, recently emerged subgenogroups. In mainland China, a different situation was observed. The first outbreak, localized in Shangdong Province, was reported in 2007, and was followed by a wide-spread outbreak in mainland China in 2008. Since then, numbers of reported HFMD cases have been persistently high. Methodology/Principal Findings: To gain insight in the epidemiological behavior of EV71 in China, we studied genetic diversity and EV71 population dynamics to address whether the increase in number of reported EV71 infections reflects a real increase in viral spread or is just the result of increased awareness and surveillance. We used systematically collected VP1 gene sequences of 257 EV71 strains collected in Guangdong province from 2008 to 2010 as part of HFMD surveillance activities, and supplemented them with 305 GenBank EV71 reference stains collected in China from 1998 to 2010. All isolates from Guangdong Province belonged to subgenogroup C4. Viral population dynamics indicated that the increased reporting of HFMD in China since 2007 reflects a real increase in viral spread and continued replacement of viral lineages through time. Amino acid sequence comparisons revealed substitution of amino acid in residues 22, 145 and 289 through time regularly with the VP1 gene of EV71 strains isolated in mainland China from 1998 to 2010. Conclusions: EV71 strains isolated in mainland China mainly belonged to subgenogroup C4. There was exponential growth of the EV71 virus population in 2007 and 2008. There was amino acid substitution through time regularly with the VP1 gene which possibly increased viral spread and/or ability of the virus to circulate persistently among the Chinese population. [ABSTRACT FROM AUTHOR]

Background: The ceratopsians represent one of the last dinosaurian radiations. Traditionally the only universally accepted speciose clade within the group was the Ceratopsidae. However, recent discoveries and phylogenetic analyses have led to the recognition of a new speciose clade, the Leptoceratopsidae, which is predominantly known from the Upper Cretaceous of North America. Methodology/Principal Findings: Here we report a new leptoceratopsid taxon, Zhuchengceratops inexpectus gen. et sp. nov., based on a partial, articulated skeleton recovered from the Upper Cretaceous Wangshi Group of Zhucheng, Shandong Province, China. Although Zhuchengceratops is significantly different from other known leptoceratopsids, it is recovered as a derived member of the group by our phylogenetic analysis. Furthermore, Zhuchengceratops exhibits several features previously unknown in leptoceratopsids but seen in ceratopsids and their close relatives, suggesting that the distribution of morphological features within ceratopsians is more complex than previously realized. Conclusion/Significance: The discovery of Zhuchengceratops increases both the taxonomic diversity and the morphological disparity of the Leptoceratopsidae, providing further support for the hypothesis that this clade represents a successful radiation of horned dinosaurs in parallel with the Ceratopsidae in the Late Cretaceous. This documents a surprising case of the coexistence and radiation of two closely-related lineages with contrasting suites of jaw and dental features that probably reflect adaptation to different food resources. [ABSTRACT FROM AUTHOR]