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Maintaining and improving ecological resilience is of great practical significance for the Yellow River Basin to reduce potential ecological risks and deliver sustainable development. Based on the essential characteristics of evolutionary resilience, this paper developed an ecological resilience index system of "resistance-recovery-reconstruction-renewal" and calculated the ecological resilience of 75 prefecture-level cities in the Yellow River Basin from 2007 to 2021 with the improved TOPSIS method. Then the spatiotemporal evolution characteristics of ecological resilience were analyzed using the gravity center-standard deviation ellipse, Dagum Gini coefficient decomposition, and spatial autocorrelation analysis. Furthermore, the dynamic spatial Durbin model (DSDM) was used to investigate the influencing factors of ecological resilience. The main results are as follows: (1) The ecological resilience of the Yellow River Basin showed an overall fluctuating upward trend, and the average annual growth rate in the downstream region was larger than in the upstream and midstream regions. (2) Cities with similar levels of ecological resilience were distributed in a "large settlement, small scattered" pattern. The center of gravity shifted to the southeast, and the spatial distribution exhibited a "northwest-southeast" pattern and a trend towards an "east–west" pattern. The primary source of spatial differences was the intensity of transvariation. (3) The ecological resilience in the Yellow River Basin showed significant spatial clustering, with the H–H clustering area shifting from the Hubao-Eyu urban agglomeration to the Shandong Peninsula urban agglomeration, and the L–L clustering area mainly distributed around the Central Plains city cluster. (4) The ecological resilience of the Yellow River Basin exhibited significant snowball, spillover, and siphon effects in time, space, and space-time dimensions, respectively. In the short and long term, population density and openness significantly positively affected the ecological resilience of local and surrounding cities. Urbanization had a long-term effect on ecological resilience without a short-term effect. GDP per capita and industrial structure only imparted a significant positive influence on local ecological resilience. The negative spatial spillover of the intensity of financial investment in technological innovation gradually turned into a positive effect. [ABSTRACT FROM AUTHOR]

The health of young people is crucial for the future and development of a nation. It is the collective responsibility and imperative mission of society to ensure the holistic well-being, both physically and mentally, of young individuals. Therefore, it is essential to thoroughly comprehend the factors that influence their health in order to expedite the exploration of effective solutions. The objective of this study is to comprehend the mechanisms that underlie the correlation between physical exercise behavior and psychological resilience among teenagers, while also examining the mediating role played by social sensitivity and need to belong. So put forward the hypothesis: (1) physical exercise behavior can positively predict the psychological resilience. (2) Social sensitivity and need to belong plays a mediating role between physical exercise behavior and psychological resilience. (3) Social sensitivity and need to belong plays a chain mediating role between physical exercise behavior and psychological resilience. Using the cluster sampling method, a total of 1106 students (with an average age of 15.7 and a standard deviation of 0.598) who met the requirements were surveyed from Shandong Province in China. Standard scales were utilized to assess Physical Exercise Behavior, Psychological Resilience, Social Sensitivity, and Need to Belong. For data analysis, Pearson's correlation analysis and bias-corrected percentile Bootstrap method were sequentially conducted. (1) The present study did not find any significant methodological bias, and the observed correlations between physical exercise behavior, psychological resilience, social sensitivity, and need to belong were all statistically significant; (2) Based on the self-determination theory, this study elucidates the relationship between physical exercise behavior and psychological resilience among teenagers. The findings indicate that physical exercise behavior positively predicts the need to belong and psychological resilience, while negatively predicting social sensitivity. Similarly, social sensitivity negatively predicts the need to belong and psychological resilience. Moreover, the need to belong directly and positively predicts psychological resilience. Importantly, all hypotheses proposed in this paper were empirically supported. (3) The indirect effect of the path mediated by social sensitivity is 0.009, while the indirect effect of the path mediated by need to belong is 0.033. Additionally, the combined indirect effect of both social sensitivity and need to belong as mediating variables is 0.014. (4) The cumulative sum of all these indirect effects amounts to 0.056. Based on the self-determination theory, we propose a chain mediation model, specially, physical exercise behavior can significantly positively predict psychological resilience, among which, social sensitivity and need to belong play a significant mediating role between Physical exercise behavior and psychological resilience. In addition, the adoption of good physical exercise behavior can enhance the psychological resilience of adolescents by diminishing social sensitivity and augmenting the need to belong. [ABSTRACT FROM AUTHOR]

Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as an example, the data from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) is used to invert GWS fluctuation from January 2003 to December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ groundwater volume and level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), and the impact factors, such as precipitation and human activities, which are also analyzed. To predict the short-time changes of GWS, the Support Vector Machines (SVM) is adopted together with three commonly used methods Long Short-Term Memory (LSTM), Singular Spectrum Analysis (SSA), Auto-Regressive Moving Average Model (ARMA), as the comparison. The results show that: (1) The loss intensity of western GWS is significantly greater than those in coastal areas. From 2003 to 2006, GWS increased sharply; during 2007 to 2014, there exists a loss rate − 5.80 ± 2.28 mm/a of GWS; the linear trend of GWS change is − 5.39 ± 3.65 mm/a from 2015 to 2022, may be mainly due to the effect of South-to-North Water Diversion Project. The correlation coefficient between GRACE and WGHM is 0.67, which is consistent with in-situ groundwater volume and level. (2) The GWS has higher positive correlation with monthly Global Precipitation Climatology Project (GPCP) considering time delay after moving average, which has the similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, the influencing facotrs on annual GWS fluctuation are analyzed, the correlation coefficient between GWS and in-situ data including the consumption of groundwater mining, farmland irrigation is 0.80, 0.71, respectively. (3) For the GWS prediction, SVM method is adopted to analyze, three training samples with 180, 204 and 228 months are established with the goodness-of-fit all higher than 0.97. The correlation coefficients are 0.56, 0.75, 0.68; RMSE is 5.26, 4.42, 5.65 mm; NSE is 0.28, 0.43, 0.36, respectively. The performance of SVM model is better than the other methods for the short-term prediction. [ABSTRACT FROM AUTHOR]

Land cover change affects the carbon emissions of ecosystems in some way. The qualitative and quantitative understanding of carbon emissions from human activities (e.g., land cover change, industrial production, etc.) is highly significant for realizing the objective of carbon neutrality. Therefore, this paper used GlobeLand30 land cover maps, annual average normalised difference vegetation index (NDVI) data, annual average net ecosystem productivity (NEP) data and statistical yearbook data from 2000 to 2020 to explore the relationship between land cover change and carbon emissions. Specifically, it included land cover change, carbon storage changes influenced by land cover change, spatial and temporal analysis of carbon sources and sinks, land use intensity change and anthropogenic carbon emissions. The results of the study show that the main land cover changes in Shandong province during 2000–2020 was cultivated land conversion to artificial surfaces. Among them, the area of cultivated land converted to artificial surfaces from 2000 to 2010 was 4930.62 km2, and the proportion of cultivated land converted to artificial surfaces from 2010 to 2020 was as high as 78.35%. The total carbon stock of vegetation affected by land cover change decreased by 463.96 × 104 t and 193.50 × 104 t in 2000–2010 and 2010–2020 respectively. The spatial and temporal distribution of carbon sources and sinks differed more markedly from 2000 to 2020, and land use intensity changes in Shandong Province showed an upward trend. Of the total energy production, industry has the largest energy consumption, followed closely by total energy consumption in transportation, storage and postal services. [ABSTRACT FROM AUTHOR]

China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000–2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000–2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies. [ABSTRACT FROM AUTHOR]

To investigate the stability of a super-large section chamber group, an analysis was conducted based on the in-situ geological conditions of a super-large section chamber group utilized as a coal gangue separation system at the Longgu Coal Mine. Field measurement and numerical simulation were employed to analyze the failure area and stress state of the surrounding rock under varying chamber spacings. The results indicate that the extent of the plastic zone significantly expands when the spacing between chambers is less than 2.0 times the chamber width. When the distance between chambers is 1.5 times the chamber width, it results in the rock pillars being entirely within the plastic zone. As the chamber spacing decreases, the tangential stress within the rock pillar range increases. When the chamber spacing is 2.5, 2.0, and 1.5 times the chamber width, the maximum tangential stress is 1.19, 1.46, and 1.18 times that in the case of a single chamber, respectively. Based on the displacement analysis, it was observed that as the distance between the chambers decreases, there is a notable increase in the displacement of the pillar sides and chamber top, indicating a higher risk of collapse. Integrating the plastic area and stress analysis allows for the categorization of the rock pillar area into four sections: the broken area, loose area, stable area, and firm area. Drawing upon the theoretical solution of the plastic zone of a circular chamber and the equivalent radius method, an approximate solution for the plastic zone of a non-circular chamber has been provided. Furthermore, the minimum reasonable spacing between chambers in a super-large section chamber group is provided as a distance criterion for the failure of a double chamber. [ABSTRACT FROM AUTHOR]

Improving access to HIV/AIDS healthcare services is of great concern to government and policymakers striving to strengthen overall public health. How to reasonably allocate HIV/AIDS healthcare resources and maximize the equality of access to healthcare services across subdistrict areas has become an urgent problem to be solved. However, there is limited research on this topic in China. It is necessary to evaluate spatial accessibility to improve the accessibility and equity of HIV/AIDS healthcare services. In this study, the improved multi-modal two-step floating catchment area (2SFCA) and inverted 2SFCA (i2SFCA) methods are used to measure the spatial accessibility of HIV/AIDS healthcare services and the crowdedness of the healthcare sites in Shandong Province, China. Then, the theoretical supply and the optimal spatial distribution of resources are calculated and visualized by minimizing the accessibility gaps between demand locations. This study showed that the spatial accessibility of HIV/AIDS service resources in Shandong Province was concentrated and unevenly distributed, and the accessibility scores in the marginal areas of prefecture-level cities were significantly lower than those in other areas. Regions with a large number of doctors had significantly higher levels of spatial accessibility. The ART accessibility scores in the southwest of Shandong Province were higher than those in other regions. As the travel friction coefficient increased, the accessibility scores formed an approximately circular cluster distribution centered on the healthcare sites in geographical distribution. More ART drugs needed to be supplied in marginal areas and more doctors were needed to work on HIV/AIDS in urban areas to address the spatial distribution imbalance of HIV/AIDS healthcare services. This study profoundly analyzed the spatial accessibility of HIV/AIDS healthcare services and provided essential references for decision-makers. In addition, it gives a significant exploration for achieving the goal of equal access to HIV/AIDS healthcare services in the future. [ABSTRACT FROM AUTHOR]

Temperature as an important indicator of climate change, accurate temperature prediction has important guidance and application value for agricultural production, energy management and disaster warning. Based on the advantages of CEEMDAN model in effectively extracting the time–frequency characteristics of nonlinear and nonsmooth signals, BO algorithm in optimizing the objective function within a limited number of iterations, and BiLSTM model in revealing the connection between the current data, the previous data and the future data, a monthly average temperature prediction model based on CEEMDAN–BO–BiLSTM is established. A CEEMDAN–BO–BiLSTM-based monthly average temperature prediction model is developed and applied to the prediction of monthly average temperature in Jinan City, Shandong Province. The results show that the constructed monthly mean temperature prediction model based on CEEMDAN–BO–BiLSTM is feasible; the constructed CEEMDAN–BO–BiLSTM model has an average absolute error of 1.17, a root mean square error of 1.43, an average absolute percentage error of 0.31%, which is better than CEEMDAN–BiLSTM, EMD–BiLSTM, and BiLSTM models in terms of prediction accuracy and shows better adaptability; the constructed CEEMDAN–BO–BiLSTM model illustrates that the model is not over-modeled and adds complexity using Friedman's test and performance comparisons between model run speeds. The model provides insights for effective forecasting of monthly mean temperatures. [ABSTRACT FROM AUTHOR]

The Yellow River Basin has a wealth of tourism resources, a long history of folk sports, and strong legislative support, all of which are advantages for the growth of the sports tourism sector. This study constructs an evaluation index system based on panel data from nine provinces and regions in the Yellow River Basin from 2011 to 2020, and then measures the development index and analyzes the driving factors using the entropy method, coupling coordination degree model, kernel density estimation method, and grey correlation analysis method. The findings demonstrate that (1) the Yellow River Basin's overall level of growth in the sports and tourist sectors exhibits a consistent and upward trend and that Shandong and Henan provinces clearly have an edge over other provinces in terms of development. (2) The geographical development pattern was lower Yellow River > upper Yellow River > middle Yellow River, and the coupling coordination status shifted from slight disorder to good coordination. (3) There is a close connection between sports tourism and variables including population density, financial prowess, and infrastructure growth. The employment population index has the smallest link with invention patent authorization. The macro-policy framework should therefore be strengthened in the future, the sports tourism infrastructure should be improved, and the Yellow River basin's unique sports tourism resources should be fully utilized in order to increase brand influence. In addition, new sports tourism products should be developed in response to market demand and consumer preferences, and enterprise innovation and research and development efforts should be increased in order to achieve high-quality development transformation. [ABSTRACT FROM AUTHOR]

We studied the effectiveness of movie character analysis for teaching psychotic symptomatology to medical undergraduates. We randomly selected two of six medical schools in Shandong Province, China, then randomly assigned eight undergraduate classes at those schools to intervention or control groups. The intervention group (n = 162) participated in seminars in which psychotic symptoms were explored through analysis of movie characters. The control group (n = 165) participated in conventional seminars. The participants in both groups were surveyed with a custom-designed questionnaire, and their knowledge was assessed using a written exam. Compared to the control group, the intervention group showed greater interest in the topic (t = 5.63, p < 0.001), better understanding of psychotic symptoms (t = 2.37, p = 0.02), and greater acceptance (t = 9.80, p < 0.001). In addition, the intervention group showed significantly greater knowledge on the written exam (t = 5.78, p < 0.001). Analyzing movie characters can improve the teaching of psychotic symptomatology and should be further explored and promoted. [ABSTRACT FROM AUTHOR]

niversity stage, especially the freshmen stage, is a high incidence stage of students' psychological problems. Effective sampling investigation and statistical analysis of freshmen's mental health problems are conducive to solve freshmen's problems and prevent further crises. In the past 4 years (2018–2021), using Chinese college students' mental health screening scale, we have taken probability proportionate to size sampling investigations about the mental problems to 9882 freshmen in 45 public universities in Shandong Province near the end of their first semester. Based on these data, we conducted the comparison of anxiety and depression for post pandemic era vs. pre pandemic era by analysis of variance, and analysed the influencing factors for anxiety and depression by linear regression and canonical correlation analysis. The results indicate the extents of anxiety and depression in post pandemic era are significantly more severe than pre pandemic era. Inferiority complex, obsession and somatization are the main effect factors of anxiety and depression. To the best of our knowledge, this research is the first systematical investigation and analysis for the mental problems among freshmen in the whole Shandong Province before and after the epidemic. The research results are conducive for the mental health counseling and intervention of freshmen's mental problems, and also helpful for policy making and prevention for psychological crisis management. [ABSTRACT FROM AUTHOR]

Based on nighttime light data and statistical data, this study calculated the level of urban–rural integration (URI) of Shandong province, researched spatial heterogeneity of URI levels by local spatial autocorrelation analysis, Geodetector, and geographically weighted regression, and analyzed its influencing factors and spatial heterogeneity. The results concluded that: (1) The spatial pattern of urban–rural integrated level is consistent with the level of regional economic development in Shandong province. The level of URI is higher along the Qingdao–Jinan railway and along the coast, whereas the level is lower in southwest Shandong and northwest Shandong. (2) The cities of Yantai and Weifang are High–High cluster areas of urban integration, and Jining is a Low–Low cluster area. The spatial agglomeration characteristics are not significant in other cities. (3) Among the main factors affecting URI, the explanatory power of the rural population with high school or technical secondary school education or above, the area of urban construction land, and the secondary and tertiary industry GDP to the spatial pattern of URI in Shandong province are 73.58%, 62.08%, and 58.66%, respectively. As the key factors, spatial heterogeneity, such as north–south differences, southwest-to-northeast differences, and east–west differences, is evident. [ABSTRACT FROM AUTHOR]

Due to global warming, global and regional extreme precipitation events occur frequently, causing severe drought and flood disasters. This has a significant impact on productivity and human life. Therefore, it is of great significance to study the characteristics of extreme precipitation and its spatiotemporal variation. In this study, we investigate the dominant variation patterns of extreme precipitation (EP), which is characterized by indices, and also analyze its potential causes in the Shandong province of China during 1961–2015 using the daily precipitation data from 123 metrological stations. The results show that there has been a dry trend in the Shandong Province in the past 55 years, that is, with the decrease in precipitation, most of the extreme precipitation index has basically showed a downward trend to varying degrees. In particular, the increase in the number of consecutive dry days (CDD) and the decrease in the number of consecutive wet days (CWD) can better explain the drought in this region. After the 1980s, the extreme precipitation index basically showed an upward trend to varying degrees, indicating that extreme precipitation events have shown an increasing trend in recent years. The spatial distribution of each extreme precipitation index generally increased from north to south. The mutation of each extreme precipitation index occurred in the 1970s and 1990s, and there was a main period of 0.9–2.2 years. In terms of influencing factors, the NINO3 area can be used as the critical sea area for the response of extreme precipitation to SSTAs in the Shandong Province. The research results are helpful to understand the temporal and spatial variations of extreme precipitation and have very important reference value for the prediction of and response to climate change and extreme events in the future. [ABSTRACT FROM AUTHOR]