Notable Positive Effect Research Articles

Transforming Manufacturing Service Quality through Enhanced Innovation Capabilities

This study is an empirical investigation conducted within a manufacturing industry in Tangerang. The primary objective of the research is to analyze how innovation capability and work productivity impact the service quality provided by workers to customers. Data collection was carried out using questionnaires distributed through a random sampling method to all permanent employees in the industry, resulting in 115 valid responses. The data analysis was performed using the Structural Equation Modeling (SEM) technique with SmartPLS 3.0 software. The findings indicate that both innovation capabilities and work productivity significantly and positively affect service quality. Additionally, innovation capability also has a notable positive effect on work productivity. This research proposes a model aimed at enhancing service quality in the manufacturing sector by improving workers' innovation capabilities and productivity. Ultimately, this study could help prepare both workers and companies to thrive in the context of the industrial revolution 4.0.

Does Oil Prices Impact Sectoral Stock Market Prices? Evidence from Emerging Economies

This study investigates the effect of oil price (OPs) shocks on stock market prices (SMPs) of 48 listed companies in all sectors of the Muscat Stock Exchange (MSX) in the Sultanate of Oman. The analysis is based on monthly data collected from three main sectors (Finance, industry, and service) listed in MSX and intermediate international oil prices from 2009 to 2020. An alternative asset pricing model is used based on the Arbitrage Pricing Theory (APT). The model evaluated the correlation between independent factors, including oil price, interest rate, industrial production, and stock returns as the dependent variable. The analysis shows that oil price volatility has a notable positive effect on stock market prices across all sectors of listed companies on the (MSX) in the Sultanate of Oman. These findings may provide insight to policymakers to continue taking appropriate action during oil price shocks and for investors to take their decisions properly. The current study contributes to the existing literature by examining the impact of oil price shocks on stock prices in the Sultanate of Oman, GGC, and the Middle East, addressing a gap in the research.

Effect of Powdered Lemon Grass (Cymbopogon citratus) as Feed Supplement on the Growth Performance of Native Chicken

This study was conducted to determine the growth performance of the native chicken using different levels of powdered lemon grass as feed supplement in the diet. The study utilized 128 unsexed native chickens were randomly distributed into 4 experimental treatments with 4 replications and 8 birds per treatment using Randomized Complete Block Design (RCBD). The different levels of powdered lemon grass in treatments were T1 (Control) – 0%, T2 –1%, T3 –1.5%, and T4 - 2.5% powdered lemon grass, respectively. The results revealed that there is no significant difference in the body weight gain and feed conversion ratio of the native chicken among the experimental animals. In the feed consumption, there is a highly significant difference among the treatment mean during week 2 and 8, and significant difference on week 4, 11 and 12. These findings suggest that the inclusion of powdered lemongrass influenced the feed consumption of the chickens, particularly in certain periods of the study. This implies that while powdered lemongrass, particularly at 1%, appeared to enhance feed consumption during specific weeks. In terms of the average daily gain, results revealed a significant difference only in week 14. The result suggests that while the inclusion of powdered lemongrass in the diet did not significantly affect ADG during the early and middle stages of growth, it exhibited a notable positive effect in the later stages. This indicate a cumulative or delayed impact of lemongrass supplementation on growth performance, which becomes evident as the birds approach maturity. Based on the findings stated above, it can be concluded that the body weight, feed consumption, FCR and ADG of the experimental birds were affected by the different inclusion levels of powdered lemon grass. Inclusion of 1% lemon grass powder in feedstuff is recommended as it enhanced the overall growth performance of native chickens.

The Impact of Multidimensional Perceived Value on Purchase Intentions for Prepared Dishes in China: The Mediating Role of Behavioral Attitudes and the Moderating Effect of Time Pressure.

Accompanied by the flourishing development of China's prepared dishes industry, understanding consumer purchasing decisions helps companies clarify market needs and expectations. This study analyzed consumers' willingness to purchase prepared dishes and the moderating role of time pressure using the Theory of Planned Behavior and Structural Equation Modeling. Four hundred and three completed respondents were collected through an online survey of consumers in Beijing, the Capital of China. Our results showed that: (1) Respondents of various demographics (e.g., age, education, occupation, and marital status) had significant differences in willingness to buy. (2) All dimensions of value (functional, emotional, and convenience) had a notable positive effect on behavioral attitudes. However, behavioral attitudes only served as a full mediator between functional value, emotional value, and purchase intentions. (3) Time pressure played a positive moderating role in the effect of perceived value on behavioral attitudes, with positive tendencies in behavioral attitudes increasing as time pressure increased. The study concludes with recommendations for consumers, enterprises, and the government and provides an additional reference for the policy of "Strengthening Food Safety Regulation of Prepared Dishes".

An empirical study on smart city construction to enhance residents’ participation in physical activity

Smart city construction, as a new model of urban development, has become a crucial means to encourage residents’ participation in physical exercise. However, there is still a lack of systematic exploration regarding the mechanisms by which smart city construction specifically affects residents’ engagement in physical activity. This paper analyzes the impact of smart city construction on residents’ participation in physical activity using a Difference-in-Differences (DID) model, based on data from the 2010 to 2020 China Family Panel Studies (CFPS). Data processing involved removing missing values, addressing outliers, and introducing control variables at the individual, household, and city levels. The study found that smart city construction significantly promotes residents’ participation in physical activity. Smart city policies have a notable positive effect on this participation, and there are significant differences in the responses of various resident groups to physical activity engagement. The results of the mediation analysis indicate that the built environment, information access channels, and enjoyment of consumption play significant mediating roles between smart city policies and residents’ participation in physical activity. Smart city construction influences residents’ participation in physical activity both directly or indirectly by enhancing urban infrastructure, expanding access to information, and fostering enjoyable consumption experiences. In the future, smart city initiatives should prioritize the equitable distribution of resources, strengthen infrastructure development in rural and western regions, and further enhance the national fitness level.

Development of a Green Banking and Green Financing Practice Model for Enhancing Sustainability Development Goals (SDGS)

Objective: This study is to investigate a green banking model based on green banking practices, green financing, and green environment to enhance sustainability development goals (SDGs). Theoretical Framework: The research focuses on developing green banking and financing practices to improve environmental performance in the Indonesian banking sector. Green Banking emphasizes sustainability in banking operations and products, while Green Financing promotes funding environmentally friendly projects. The study also draws on Stakeholder Theory, highlighting that banks are accountable to a wide range of stakeholders. Method: The research stages include the development of instruments, questionnaire distribution, data collection, and data processing using a sample of 54 respondents, selected using convenience sampling. Data testing and processing were carried out using SmartPLS software. Results and Discussion: The analysis of banking employees and practitioners revealed that Banks' Customer-Related Practices (BCRP), Employee-Related Practices (BERP), and Operation-Related Practices (BORP) positively impact Green Environment Performance (GEP), whereas Banks' Policy-Related Practices (BPRP) do not. Additionally, while BCRP, BERP, and BORP showed no significant influence on Green Financing (GF), BPRP demonstrated a notable positive effect on Green Financing (GF). This result also show that Studies on Bank’s customer behavior change towards sustainability and its influence on the SDGs. Research Implications: Banks can implement specific green practices to improve their sustainability development goals (SDGs). The study reinforces Sustainability Theory by highlighting the importance of balancing environmental, social, and economic concerns in banking operations, confirming the need for a "Triple Bottom Line" approach in business models. Originality/Value: The originality of the research is demonstrated through its Studies on Bank’s customer behavior change towards sustainability and its influence on the SDGs by integrating multiple theoretical perspectives.

E-Governance and Service Delivery by Rwanda National Public Service Commission

Purpose: This study examined the effect of E-governance and service delivery by Rwanda National Public Service Commission. The specific objectives of this study included, determining the effect of E-administration on service delivery by Rwanda National Public Service Commission and determining the effect of E-participation on service delivery by Rwanda National Public Service Commission. The three theories that provided the basis of this research are the following: Stakeholders Theory, Technology Acceptance Model and Expectancy Disconfirmation Theory. Chose these ideas because of what they have to say about how services are provided in a tech-driven setting. In order to accomplish these goals, an analysis of relevant literature was conducted. Methodology: Data were gathered from 47 randomly selected workers of the Rwanda National Public Service Commission using a census sample approach. Data was gathered using a combination of questionnaires and document analysis. As part of the study, SPSS 25 was used. Findings: The Rwanda National Public Service Commission found a high level of correlation (R = 0.844) between the predictors of service delivery and administration, and participation. With an R-squared value of 0.712, these variables account for around 71.2% of the variance in service delivery. Their unstandardized coefficients emphasize the impact of each predictor on service delivery. With a coefficient E-administration also has a notable positive effect, with a coefficient of (β = 0.404, t = 4.646, and p-value = 0.000). Similarly, E-participation contributes positively, with a coefficient of (β = 0.505, t = 5.973, and p-value = 0.000). All coefficients are statistically significant, underscoring their crucial roles in enhancing service delivery, as indicated by their p-values being below the conventional threshold of 0.05. Unique Contribution to Theory, Practice and Policy: The study recommended that Rwanda National Public Service Commission should enhance the user interface and accessibility of online platforms, expand online services while integrating with other government systems, and improve cybersecurity protocols.

How Do Greenhouse Gases and Other Factors Affect Rice Production in Bangladesh? An Insight from Autoregressive Distributed Lag Approach

Purpose: The study aims to elucidate the impact of greenhouse gases and other factors on rice production in Bangladesh. By considering the influences of greenhouse gases, technological factors, and industrial activities, the research unveils significant insights into the long-term and short-term effects on rice production. Methodology: This research employs the Autoregressive Distributed Lag (ARDL) approach to investigate the impact of carbon dioxide, nitrous oxide, agricultural land, agriculture as percentage share of GDP, and industry on rice production in Bangladesh through EViews-12 Software. Findings: Our findings suggest that CO2 emissions, industrial and agricultural share as percentage of GDP exhibit a negative impact, decreasing rice production, while N2O and agricultural land have a notable positive effect. Technical factors such as the area under rice cultivation, agriculture and industry are identified as pivotal contributors to rice production. Practical Implications: Finally, the study concludes with policy implications and recommendations based on our findings for sustainable agricultural practices, technological advancements, and policy interventions tailored to enhance rice production and secure food sustainability in the unique agricultural landscape of Bangladesh. Originality/Value: As per as our knowledge, no research has been carried out in Bangladesh to investigate the impact of greenhouse gases and selected factors on rice production. Research Limitations: Due to difficulties in data collection procedure, we could not include all variables of greenhouse gases. We expect in future, there will be more data sources which would help many researchers to contribute to rice production related researches.

The efficacy of some endophytic fungi against primary grapevine black foot disease pathogens

ABSTRACT Black foot disease (BFD), primarily attributed to taxa within the genera Dactylonectria and Ilyonectria, is a significant problem that causes serious damage worldwide in many grape and wine regions. This threat could especially be destructive in nurseries and early-stage vineyards, where it induces a decline in growth along with drying, leading to a reduction in the quality and lifespan of the grapevines. This research mainly focused on assessing the biocontrol capabilities of endophytic isolates derived from grapevine saplings, specifically Acremonium sclerotigenum and Clonostachys rosea. The study aimed to assess their effectiveness against the major pathogens responsible for BFD, including Dactylonectria macrodidyma, D. torresensis, and I. liriodendri, under laboratory and in vivo conditions. In the conducted paired culture assays, Trichoderma harzianum KRL-AG2 was employed for comparative purposes. On the 28th day of antagonistic tests, the inhibition response of A. sclerotigenum (≥94%) and C. rosea (>90%) isolates against the three species of BFD, D. macrodidyma, D. torresensis, and I. liriodendri, reached the maximum inhibition rate. Based on the in vivo analysis conducted with 1103 P rootstocks, T. harzianum, A. sclerotigenum, and C. rosea isolates significantly reduced the disease severity and supplied notable positive effects on plant growth parameters, including root dry weight, root length, and shoot dry weight. These results suggest that these biocontrol agents have potential for the biological management of BFD.

Using iron speciation to track hydrocarbon migration in bleached rocks and its implications for reservoir reconstruction

Bleaching of red rock beds by hydrocarbons can provide valuable insights for hydrocarbon migration and reservoir transformation. This study investigated the bleaching effects of hydrocarbons on various rock types in the Dushanzi mud volcanic area. Bedrock and bleached samples of different lithologies, including mudstone, sandy mudstone and sandstone, were systematically collected and analyzed for their iron species, mineralogical and chemical compositions using Mössbauer spectroscopy, X-ray diffraction and X-ray fluorescence, respectively. The results indicate that the iron species of the studied samples were dominated by para-Fe3+ (from 44% to 76%), with variable contents of mag-Fe3+, para-Fe2+ and pyr-Fe2+. When compared to the related unbleached rocks, the bleached rocks exhibited a higher proportion of reduced Fe (para-Fe2+ and pyr-Fe2+). The pyr-Fe2+ in the sandstones and sandy mudstones was significantly higher than that of the mudstone interlayers. The observed variations in iron species were consistent with changes in mineralogical and chemical compositions, which can be correlated with the petrological properties of rocks. The increase of quartz and decrease of feldspar and carbonates in the bleached rocks could be attributed to the dissolution of feldspar and the subsequent secondary enlargement of quartz. Geofluids containing crude oils and natural gases preferentially dissolved K-feldspar over albite. The bleached rocks had a significant decrease in the proportion of kaolinite and a slight decrease in the proportion of chlorite, while the proportions of smectite and illite were increased. The dissolution of K-feldspar could provide sufficient K+ for the formation of illite, and the appearance of smectite in the bleached samples might be related to the dissolution of albite in an alkaline environment. The dissolution of carbonates and feldspar, along with the transformation of clay minerals, had a notable positive effect on the formation of secondary porosity, facilitating hydrocarbon migration. These findings provide valuable insights into the interactions between hydrocarbons and different lithologies, informing the impact of hydrocarbon migration on reservoir reconstruction in similar geological settings.

Impact of Industry Digitization on ESG Performance – An Empirical Analysis Based on Industry Perspective

This research seeks to investigate the influence of industrial digitalization on environmental, social responsibility, and corporate governance (ESG) outcomes. Through the utilization of a panel data model, the study demonstrates that the industrial digitalization index exerts a notable positive effect on corporate ESG performance, with this impact displaying a gradual augmentation in recent periods. The findings elucidate the correlation between industrial digitalization and ESG performance, underscoring the significance of corporate ESG ratings. Furthermore, the study contributes to the scholarly discourse on the industrial digitization process and the determinants of ESG performance, shedding light on the repercussions of digitalization advancement on industry ESG through an industry-centric lens.

Glutamic-N,N-Diacetic Acid as an Innovative Chelating Agent in Microfertilizer Development: Biodegradability, Lettuce Growth Promotion, and Impact on Endospheric Bacterial Communities

The search for new biodegradable fertilizers to increase the productivity of agricultural plants is an urgent task. In this study, a complex microfertilizer was developed based on a chelating agent—glutamic-N,N-diacetic acid (GLDA). The evaluation encompassed assessments of biodegradability and effectiveness in fostering lettuce plant growth in hydroponic and conventional soil settings. The impact on endospheric bacteria, a sensitive indicator, was also examined. Results indicated a 59.8% degradation rate of the GLDA complex on the 28th day. The most notable positive effects were observed in above-ground plant biomass, with a 4.6-fold increase for hydroponics and 1.5 to 1.8-fold increases for root and foliar treatments in soil. In hydroponics, GLDA-treated plants showed 24 and 45 operational taxonomic units (OTUs) for leaves and 272 and 258 for roots (GLDA-treated and control plants). In soil, the OTU counts were 270 and 101, 221 and 111, and 198 and 116 in the leaves and roots of GLDA-treated and control plants (under root and foliar treatments), respectively. Non-metric multidimensional scaling (NMDS) and Indicator Species Analysis (ISA) demonstrated significant distinctions in endospheric communities between substrates (hydroponics and soil) in the presence of GLDA. Importantly, GLDA use simplified the composition of endospheric bacterial communities.

Is the Tour Guide’s Competency Important to Increase Tourist Satisfaction?

As frontline workers who interact with tourists, tour guides play an essential role in improving the travel experience and creating tourist satisfaction. Consequently, tour guides must possess professional competence to perform their duties effectively. This research aims to analyze the influence of tour guides' competence on tourist satisfaction at the Jakarta History Museum, a prominent tourist attraction and historical tourism asset in Jakarta. The study employed a survey method involving 100 tourists of the Jakarta History Museum who had utilized the services of tour guides as respondents. The data analysis was conducted using multiple linear regressions. The results indicated that the competence of tour guides had a positive and significant impact on tourist satisfaction. Although knowledge alone did not significantly contribute to tourist satisfaction, the professional skills and attitudes of the tour guides had a notable positive effect. The competence of tour guides accounted for 47.748% of the variation in tourist satisfaction. Therefore, enhancing the competence of tour guides is essential to ensuring tourist satisfaction.

The impact of the implementation of hierarchical medical system on population health: evidence from China

IntroductionThe implementation of a hierarchical medical system holds significant practical importance in advancing the Healthy China strategy and elevating the overall health status of the population of China.MethodsThis article empirically examines the influence of the implementation of a hierarchical medical system on the health of the population using the latest 2020 China Family Panel Studies database. Furthermore, it investigates the variability of this impact across distinct health insurance participation statuses and literacy groups.ResultsThe findings of the study demonstrate that the implementation of the hierarchical medical system substantially enhances the health of the population, not only in terms of self-assessed health but also through a notable positive effect on alleviating chronic diseases. These results maintain their validity even after conducting robustness tests utilizing a replacement estimation model. Heterogeneity analysis reveals that the impact of the hierarchical medical system on the population’s health status exhibits significant variation concerning health insurance participation and literacy. Specifically, regarding health insurance participation, the hierarchical medical system effectively improves both self-assessed health and chronic disease status among the insured population. However, for those not enrolled in health insurance, the hierarchical medical system only demonstrates improvement in chronic disease status, with insignificant results observed in enhancing self-assessed health status. Moreover, propensity score matching (PSM) was also used to address endogeneity problems resulting from sample selectivity bias. The findings demonstrate that endogeneity issues can be suitably addressed by the PSM model. Additionally, they point out that an overestimation of the impact of the hierarchical medical system on the population’s self-assessed health state would result from failing to take sample selectivity bias into account. On the other hand, it will lead to the underestimation of the effect of the hierarchical medical system on the status of chronic diseases.DiscussionMoving forward, steadfast efforts should be directed toward further enhancing the implementation of the hierarchical medical system. This includes the comprehensive promotion and using the pivotal role of the hierarchical medical system in improving the health of the population.

Do Water Transfer Projects Promote Water Use Efficiency? Case Study of South-to-North Water Transfer Project in Yellow River Basin of China

With a huge capital and labor input influx, inter-basin water transfer (IBWT) projects have been shown to effectively mitigate water stress and ensure the water demand for social and economic development in the receiving area. Whether they have promoted the improvement of regional water use efficiency (WUE) is crucial for sustainable management of regional water resources. Targeting the South-to-North Water Transfer Project (SNWTP), the largest and most ambitious inter-basin water transfer project in China, this study establishes quantitatively econometric models to analyze the impact of different water diversion projects, specifically the eastern route of the SNWTP (ER-SNWTP), middle route of the SNWTP (MR-SNWTP), and diversion from the main stream of the Yellow River (DYR), on the regional water consumption per unit of GDP; regional water stress, water use structure, economic structure, and urbanization level are used as control variables in different types of cities in the Yellow River Basin, and some intriguing results are found. While the overall water transfer project demonstrates a positive impact on water use efficiency, the effects of the three water transfer measures vary significantly. The ER-SNWTP does not exhibit a notable positive effect on regional water use efficiency, whereas the MR-SNWTP demonstrates a significant positive impact. Interestingly, the DYR has a notable negative influence on water use efficiency in developed cities. The water use structure, shaped by the pricing, scale, and policies of different projects, emerges as a pivotal factor in explaining these differences. Finally, this paper suggests that the impact of water transfer projects on the improvement of regional water use efficiency be viewed from a more comprehensive and developmental perspective.

Co-liquefaction of α-cellulose and phycocyanin: A preliminary study

Hydrothermal liquefaction (HTL) is an efficient technology for converting biomass to platform compounds. It has great potential for reducing the dependence on fossil fuels. The HTL of waste biomass has been extensively studied in recent years due to both its environmental and economic benefits. However, most woody waste contains a large amount of cellulose, and it is difficult to be sufficiently decomposed to valuable chemicals. Phycocyanin, a key component of algae, is easily degraded under high-temperature liquefaction conditions. In this work, focusing on bio-oil generation properties, the co-liquefaction characteristics and synergistic mechanisms of α-cellulose and phycocyanin were explored. The findings revealed a maximum bio-oil yield of 33.1 wt% under the optimal conditions (300 °C for 40 min), with a notable positive synergistic effect of 13.5 wt%. Chemical composition analysis indicated distinct compositional differences between the bio-oils derived from individual and dual feedstock. The amounts of pyridine and pyrimidine compounds increased due to the enhanced co-liquefaction. The results also highlighted the influence of temperature on the degree of conversion and product distribution. Finally, preliminary chemical reaction pathway was elucidated, underscoring the potential of integrating microalgae and woody biomass for enhanced bio-oil production.

Approaches to learning and contract cheating: exploring the mediating roles of authorship perceptions

ABSTRACT As an undesired learning behavior, contract cheating has its roots in college students’ difficulties in engaging in a challenging written assessment. To better understand this process, the study collects multicampus survey data from 910 Chinese undergraduates to explore the effects of deep and surface approaches to learning on contract cheating, focusing on the mediating roles of authorship perceptions. The authorship perceptions are measured with three subfactors: understanding authorship and plagiarism (UAP), authorial approach to writing (AAW), and incorporating others’ writing (IOW). Structural equation modeling (SEM) reveals a notable positive direct effect of the surface approach to learning on contract cheating and an insignificant direct effect of the deep approach. The results further report significant indirect effects of both deep and surface approaches to learning on contract cheating via UAP and IOW, while the indirect effects via AAW are both insignificant. These results highlight the importance of providing formal and continuous pedagogical support to enhance their learning, particularly academic writing, in inhibiting contract cheating.

The plausibility of alternative data-generating mechanisms: Comment on and attempt at replication of Dishop (2022).

Dishop (see record 2022-78260-001) identifies the consensus emergence model (CEM) as a useful tool for future research on emergence but argues that autoregressive models with positive autoregressive effects are an important alternative data-generating mechanism that researchers need to rule out. Here, we acknowledge that alternative data-generating mechanisms are possibility for most, if not all, nonexperimental designs and appreciate Dishop's attempts to identify cases where the CEM could provide misleading results. However, in a series of independent simulations, we were unable to replicate two of three key analyses, and the results for the third analysis did not support the earlier conclusions. The discrepancies appear to originate from Dishop's simulation code and what appear to be inconsistent model specifications that neither simulate the models described in the article nor include notable positive autoregressive effects. We contribute to the wider literature by suggesting four key criteria that researchers can apply to evaluate the possibility of alternative data-generating mechanisms: Theory, parameter recovery, fit to real data, and context. Applied to autoregressive effects and emergence data, these criteria reveal that (a) theory in psychology would generally suggest negative instead of positive autoregressive effects for behavior, (b) it is challenging to recover true autoregressive parameters from simulated data, and (c) that real data sets across a number of different contexts show little to no evidence for autoregressive effects. Instead, our analyses suggest that CEM results are congruent with the temporal changes occurring within groups and that autoregressive effects do not lead to spurious CEM results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation

Accurate air quality index (AQI) prediction is essential in environmental monitoring and management. Given that previous studies neglect the importance of uncertainty estimation and the necessity of constraining the output during prediction, we proposed a new hybrid model, namely TMSSICX, to forecast the AQI of multiple cities. Firstly, time-varying filtered based empirical mode decomposition (TVFEMD) was adopted to decompose the AQI sequence into multiple internal mode functions (IMF) components. Secondly, multi-scale fuzzy entropy (MFE) was applied to evaluate the complexity of each IMF component and clustered them into high and low-frequency portions. In addition, the high-frequency portion was secondarily decomposed by successive variational mode decomposition (SVMD) to reduce volatility. Then, six air pollutant concentrations, namely CO, SO2, PM2.5, PM10, O3, and NO2, were used as inputs. The secondary decomposition and preliminary portion were employed as the outputs for the bidirectional long short-term memory network optimized by the snake optimization algorithm (SOABiLSTM) and improved Catboost (ICatboost), respectively. Furthermore, extreme gradient boosting (XGBoost) was applied to ensemble each predicted sub-model to acquire the consequence. Ultimately, we introduced adaptive kernel density estimation (AKDE) for interval estimation. The empirical outcome indicated the TMSSICX model achieved the best performance among the other 23 models across all datasets. Moreover, implementing the XGBoost to ensemble each predicted sub-model led to an 8.73%, 8.94%, and 0.19% reduction in RMSE, compared to SVM. Additionally, by utilizing SHapley Additive exPlanations (SHAP) to assess the impact of the six pollutant concentrations on AQI, the results reveal that PM2.5 and PM10 had the most notable positive effects on the long-term trend of AQI. We hope this model can provide guidance for air quality management.

Urban public services and fertility intentions of internal migrants in China.

As China continues to implement its progressive fertility promotion policy, there has been a drastic decline in the fertility rate. Given that the migrant population constitutes more than a quarter of China's total population, enhancing the willingness of this demographic to have additional children through policy-guided urban public services is pivotal for optimizing China's population development strategy. This study analyzes the influence of urban public services on the reproductive intentions of the migrant population, utilizing data from 110,667 migrant families with one child, drawn from China's Migrant Population Dynamic Monitoring data in 2016 and 2018. The data analysis reveals several key findings: (1) Urban public services, overall, exhibit a notable positive effect on the willingness of the migrant population to have more children, albeit with limitations and a declining trend. (2) Among urban public services, primary basic education significantly impacts the willingness of the migrant population to expand their families. (3) Large cities have created a 'reverse screening' effect on the migrant population, leading to differential access to public services. This scenario caters effectively to the high human capital migrant individuals while reducing accessibility to livelihood public services for the low human capital migrant population. This paper critically evaluates China's progressively adjusted fertility policy from the perspective of the migrant population. It underscores the necessity of establishing a comprehensive fertility support policy system across China.