Life Satisfaction Trajectories During the Transition from Adolescence to Emerging Adulthood and the Role of Gender and Achievement Attribution: A Longitudinal Study of Chinese Youth

Life satisfaction is vital for a smooth transition to emerging adulthood. However, research on age and gender-related fluctuations in life satisfaction has yielded inconclusive and culture-specific results, which necessitates further investigation in more diverse contexts, including the Chinese culture. Despite the attribution theory and the value-as-a-moderator model highlighting the significance of achievement attribution in this period characterized by the pursuit of success, little is known about the specific impact of internal and external achievement attribution on the development of life satisfaction. This study examined life satisfaction trajectories from adolescence to emerging adulthood and explored the moderating effects of gender and achievement attribution, using five waves of data from the China Family Panel Studies (CFPS). The sample consists of 504 youth (52.2% female), whose life satisfaction was tracked from 2012 (Mage = 16.55, SD = 0.50) to 2020 (Mage = 24.56, SD = 0.50). The multilevel growth models revealed that life satisfaction increased from ages 16 to 18, peaked at age 18, fell until age 20, and then remained stable from ages 20 to 24. No significant association was found between gender or external achievement attribution and life satisfaction development. Youth with higher internal achievement attribution had a greater increase in life satisfaction from ages 16 to 18, but had a larger decrease from ages 18 to 20. Adjusting internal achievement attribution may help alleviate the vulnerability of youth experiencing declining life satisfaction when transitioning to adulthood.

Psychometric properties of the Chinese version of the 15-item Need for Closure Scale: Scale validation and associations with mental health

BACKGROUND

Need for closure (NFC) has been found to be implicated in different forms of psychopathology. The 15-item Need for Closure Scale (NFCS) is an efficient and easy tool for assessing individuals' NFC in Western contexts. However, the psychometric properties of the 15-item NFCS have not yet been validated in Chinese populations.

METHODS

Two different samples of university students from China were recruited in this study. The first sample (N = 5080, 49.9% females) was used to conduct exploratory factor analysis and reliability analysis. The second sample (N = 3968, 64.2% females) was used to perform confirmatory factor analysis, exploratory structural equation modeling (ESEM), and bifactor models, followed by tests of measurement invariance and criterion validity.

RESULTS

The full scale showed good internal consistency. The bifactor-ESEM result with a general factor and four specific factors was chosen as our final model. Strong measurement invariance across sex and ethnicity groups was supported. Evidence was obtained for the criterion validity of NFCS scores with respect to depression, anxiety, and psychological distress.

CONCLUSION

The Chinese NFCS appears to be a valid and reliable instrument for measuring the NFC, which could promote both the assessment and research of the NFC in Chinese populations.

Analysis of factors associated with depressive symptoms in stroke patients based on a national cross-sectional study

Post-stroke depression is commonly experienced by stroke survivors and has a significant negative impact on the physical, cognitive, and social functioning of those affected. This study aims to investigate the prevalence of depressive symptoms and their associated factors in Chinese stroke patients. Research samples were selected from the China Health and Retirement Longitudinal Study 2018 survey. Depression was evaluated using the 10-item Center for Epidemiological Studies Depression Scale, with a score ≥ 10 defined as depression. Univariate and multivariable analyses were performed to examine the associations of depressive symptoms with demographics, family relationships, health status, and lifestyle. A total of 963 stroke patients were included and 57.8% of them had depressive symptoms. Depressive symptoms were significantly associated with female sex (OR 1.762, 95% CI 1.235-2.514), lower education level (non-formal education: OR 2.148, 95% CI 1.235-3.737, primary to secondary school education: OR 1.964, 95% CI 1.272-3.033), dissatisfaction with spouse (OR 1.912, 95% CI 1.075-3.401), dissatisfaction with life (OR 1.779, 95% CI 1.080-2.931), dissatisfaction with health (OR 1.592, 95% CI 1.138-2.226), pain (OR 1.392, 95% CI 1.005-1.928) and abnormal sleep (OR 1.557, 95% CI 1.126-2.152). The findings suggest the need for regular depression screening and evaluation after a stroke, and that a well-functioning support system, effective health management, and lifestyle modifications could potentially improve the mental state of stroke patients.

Lifestyle behaviors and risk of cardiovascular disease and prognosis among individuals with cardiovascular disease: a systematic review and meta-analysis of 71 prospective cohort studies

BACKGROUND

Healthy lifestyle behaviors (LBs) have been widely recommended for the prevention and management of cardiovascular disease (CVD). Despite a large number of studies exploring the association between combined LBs and CVD, a notable gap exists in integration of relevant literatures. We conducted a systematic review and meta-analysis of prospective cohort studies to analyze the correlation between combined LBs and the occurrence of CVD, as well as to estimate the risk of various health complications in individuals already diagnosed with CVD.

METHODS

Articles published up to February 10, 2023 were sourced through PubMed, EMBASE and Web of Science. Eligible prospective cohort studies that reported the relations of combined LBs with pre-determined outcomes were included. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated using either a fixed or random-effects model. Subgroup analysis, meta-regression, publication bias, and sensitivity analysis were as well performed.

RESULTS

In the general population, individuals with the healthiest combination of LBs exhibited a significant risk reduction of 58% for CVD and 55% for CVD mortality. For individuals diagnosed with CVD, adherence to the healthiest combination of LBs corresponded to a significant risk reduction of 62% for CVD recurrence and 67% for all-cause mortality, when compared to those with the least-healthy combination of LBs. In the analysis of dose-response relationship, for each increment of 1 healthy LB, there was a corresponding decrease in risk of 17% for CVD and 19% for CVD mortality within the general population. Similarly, among individuals diagnosed with CVD, each additional healthy LB was associated with a risk reduction of 27% for CVD recurrence and 27% for all-cause mortality.

CONCLUSIONS

Adopting healthy LBs is associated with substantial risk reduction in CVD, CVD mortality, and adverse outcomes among individuals diagnosed with CVD. Rather than focusing solely on individual healthy LB, it is advisable to advocate for the adoption of multiple LBs for the prevention and management of CVD.

TRIAL REGISTRATION

PROSPERO: CRD42023431731.

From theory to practice: Monetary policy transmission and bank risk dynamics

This paper investigates the relationship between monetary policy and bank risk-taking by introducing a model wherein banks expend a level of costly monitoring effort to select low-risk projects, thereby reducing the risk associated with the loans they grant. The impact of monetary policy on bank risk-taking is examined through both theoretical models and empirical analysis. The paper compares theoretical models with different assumptions, revealing an unambiguous negative effect without the assumption of limited liability for banks, and an ambiguous effect with the assumption of limited liability for banks, influenced by the equity ratio. The empirical model employs unique quarterly data comprising balance sheet information for top-listed banks in the U.S. banking system from 2000 to 2017. The findings indicate that low-interest rates contribute to an increase in bank risk-taking. Moreover, this effect is more pronounced after the financial crisis and weaker before the crisis. Additionally, the impact is evident for undercapitalized banks and more substantial for those financed with a higher proportion of equity.

Influence of Green Human Resource Management on firm's environmental performance: Green Employee Empowerment as a mediating factor

This research aimed to investigate the mediating function of Green Employee Empowerment (GEE) in the relationship between Green Human Resource Management practices (GHRM) and the environmental performance of small and medium-sized enterprises (SMEs) in Ghana, drawing on the Ability-Motivation-Opportunity (AMO) theory. This study assessed the hypotheses in the established research model using structural equation modeling based on data collected from 320 participants from small and medium-sized firms in Ghana. The study's results revealed that GHRM practices were significantly correlated with the firm's environmental performance. The study found significant GHRM's indirect consequences on environmental performance through GEE in all models examined. These findings suggest that GEE plays a crucial role in translating the impact of GHRM practices into improved environmental performance. The study overlooked other potential mediators or moderators in the relationship between GHRM practices and environmental performance, focusing on GEE. To better understand the complex dynamics behind GHRM techniques' environmental performance, future research might examine business culture, leadership style, and employee sustainability attitudes.

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China

In order to solve the problem of coordinated development among mining economy, social governance and environmental conservation in global resource-based cities, we choose Guangxi Zhuang Autonomous Region as the research area. The advantage of resource endowment and resource industry was measured by location quotient and input-output method. The panel data related to mining governance from 2010 to 2021 were selected to build the evaluation and coupling analysis model between mining economic, social governance and environmental conservation, and the spatial-temporal heterogeneity and coupling effect of them were analyzed by comprehensive empowerment evaluation, spatial autocorrelation analysis and barrier degree methods. The results show that: (1) Except for the overall upward trend of social governance, the development level of mining economy and environmental conservation are basically stable; (2) The resource-rich areas have obvious mining economic advantages, and the central cities have good social governance capabilities, and the environmental conservation effectiveness is uncertain; (3) The coupling effect between mining economy and social governance is stronger than that between mining economy and environment conservation, and the synergistic coupling effect of the three is relatively random. Finally, we put forward some policy response strategies to Guangxi, and theoretical and practical reference would be provided for resource-based cities around the world.

Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach

BACKGROUND

Outliers, data points that significantly deviate from the norm, can have a substantial impact on statistical inference and provide valuable insights in data analysis. Multiple methods have been developed for outlier detection, however, almost all available approaches fail to consider the spatial dependence and heterogeneity in spatial data. Spatial data has diverse formats and semantics, requiring specialized outlier detection methodology to handle these unique properties. For now, there is limited research exists on robust spatial outlier detection methods designed specifically under the spatial error model (SEM) structure.

METHOD

We propose the Spatial-Θ-Iterative Procedure for Outlier Detection (Spatial-Θ-IPOD), which utilizes a mean-shift vector to identify outliers within the SEM. Our method enables an effective detection of spatial outliers while also providing robust coefficient estimates. To assess the performance of our approach, we conducted extensive simulations and applied it to a real-world empirical study using life expectancy data from multiple countries.

RESULTS

Simulation results showed that the masking and JD (Joint Detection) indicators of our Spatial-Θ-IPOD method outperformed several commonly used methods, even in high-dimensional scenarios, demonstrating stable performance. Conversely, the Θ-IPOD method proved to be ineffective in detecting outliers when spatial correlation was present. Moreover, our model successfully provided reliable coefficient estimation alongside outlier detection. The proposed method consistently outperformed other models (both robust and non-robust) in most cases. In the empirical study, our proposed model successfully detected outliers and provided valuable insights in the modeling process.

CONCLUSIONS

Our proposed Spatial-Θ-IPOD offers an effective solution for detecting spatial outliers for SEM while providing robust coefficient estimates. Notably, our approach showcases its relative superiority even in the presence of high leverage points. By successfully identifying outliers, our method enhances the overall understanding of the data and provides valuable insights for further analysis.

Perceived HRM and turnover intentions of elderly care workers: perspective from person-job fit and institutional ownership

BACKGROUND

Although the phenomenon of high turnover rate in the elderly care industry has existed for a long time, there are few studies that have constructed frameworks to comprehensively analyze the strength of the effects of various factors on the turnover intention of elderly care workers.. This study analyzed the impact of different types of perceived human resource management practices on elderly care workers' turnover intentions and whether this relationship is moderated by person-job fit and ownership of elderly care institutions.

METHODS

This is a cross-sectional and regional survey study. The study included questionnaire survey data from a total of 305 elderly care workers from 42 elderly care institutions in 21 provinces in China during June to September 2021. Descriptive statistics, Pearson correlation coefficient, multiple regression, and heterogeneity analyses were performed.

RESULTS

Perceived work environment ( β =-0.5164, p< 0.01), perceived occupational protection ( β =-0.3390, p< 0.01), perceived welfare benefits ( β = -0.2620, p< 0.01) and perceived competency training ( β = -0.1421, p< 0.1) were all significantly and negatively related to turnover intentions, the quality of perceived work environment has the greatest impact on elderly care workers' turnover intentions. Under the moderating effects of person-job fit and ownership of elderly care institutions, there existed heterogeneity between perceived human resource management and turnover intentions among elderly care workers. High level of person-job fit and elderly care institutions' public feature can effectively weaken the negative impact of each type of perceived human resource management on turnover intention among elderly care workers.

CONCLUSIONS

The managers of elderly care institutions should optimize the management mechanism, typically pay attention to elderly care workers' working environment, formulate and improve the professional standards and job requirements for elderly care workers, promote the public welfare value of nursing care services, and strengthen the sense of honor and responsibility of elderly care workers to reduce the turnover rate.

The dynamic risk spillover effects among carbon, renewable energy, and electricity markets based on the TVP-VAR-DY model

The linkages among carbon, renewable energy, and electricity markets are gradually strengthening. In order to prevent risk transmission among markets, this paper uses the TVP-VAR-DY (Time-Varying Parameter-Vector Auto Regression-Dynamic) model to analyze the dynamic risk spillover effects and network structure of risk transmission among carbon, renewable energy, and electricity markets. The empirical results show that there are significant asymmetric spillover effects among carbon, renewable energy, and electricity markets. The total spillover index shows that spillover effects among carbon, renewable energy, and electricity markets are time-varying, especially during unexpected events. Besides, the net spillover index indicates that the spillover effects are bidirectional, asymmetric, and time-varying. Finally, under the influence of unexpected events, the network structures of risk transmission among carbon, renewable energy, and electricity markets are heterogeneous. Compared to the Russia-Ukraine conflict, the COVID-19 pandemic has a more significant impact on these markets.

The Ending Effect in the Domain of Gambling: The Effect of Gain-Loss Status on Economic Decision-Making

Previous studies have shown that people prefer risk-taking at the end of gambles, a phenomenon called the ending effect. By using the Guess Gambling Game, we investigated the impact of gain-loss status on the ending effect (Experiment 1) and whether and how this effect may be affected by time reference (Experiment 2) and gender (Experiment 1&2). In Experiment 1, we observed the ending effect only in the gain group. Furthermore, gender differences exist in the loss group behavior, females were more risk-averse than males, and males tend to investment more initially and then reduce their investment in a U-shaped pattern (Experiment 1&2). Next, in Experiment 2, the findings indicated that participants in the gain group made riskier decisions and were willing to allocate more money for additional decision opportunities, irrespective of the time conditions. Additionally, under time-limited condition, participants tended to make more decisions in the final round, aiming to maximize their choices times within the limited time. These results contribute to a better understanding of the boundary conditions surrounding the ending effect in risky decision-making and may offer a scientific basis for mitigating and intervening in irrational decision-making.

Housing debt and depressive symptoms: evidence from the China family panel studies

BACKGROUND

There is limited evidence on the association between housing debt and depressive symptoms in China. This study aimed to examine the impact of housing debt on depressive symptoms and explore the heterogeneous impacts arising from two sources of housing debt and two types of housing demands.

METHODS

Using data from the 2016 and 2018 China Family Panel Studies (CFPS), this study included 25,232 Chinese individuals. Depressive symptoms were assessed using the eight-item Center for Epidemiological Studies Depression Scale (CES-D8). Housing debt was measured by dummy variables, indicating whether an individual had housing debt, and continuous variables, which were the logarithm of the total amount of housing debt. The two-way fixed effects model was used to examine the relationship.

RESULTS

Housing debt had a significant positive impact on depressive symptoms in China. Individuals with housing debt had a 0.176-point higher depressive symptom score than those without housing debt. A 10% increase in the total amount of housing debt led to a 0.16-point increase in depressive symptoms. Non-bank housing loans significantly increased the level of depressive symptoms with a larger coefficient (coef = 0.289), while the impact of bank housing loans was small and not statistically significant. In terms of the types of housing demands, a positive impact was observed only among individuals who had only one property meeting their housing consumption demands.

CONCLUSIONS

This study found a significant positive impact of housing debt on depressive symptoms, primarily driven by non-bank housing loans. Furthermore, housing debt increased the depressive symptoms among individuals with consumption demands, while those with investment demands did not show a significant impact. Government interventions should prioritize easing formal financial constraints and providing support for individuals with housing consumption demands.

Has environmental protection tax reform promoted green transformation of enterprises? Evidence from China

Facing the increasingly stringent constraints of resources and the environment, the green transformation of enterprises is imperative. This study selects A-share listed companies in Shanghai and Shenzhen from 2014 to 2021 as samples, using the difference-in-differences method to examine the impact of the environmental protection tax reform (EPTR) on the green transformation of enterprises. The results indicate that the EPTR can promote the green transformation of enterprises, achieving this through three channels: raising the cost of pollution, strengthening the rigidity of law enforcement, and breaking the collusion between the government and enterprises. Notably, this promotional effect is more significant in non-state-owned enterprises, companies in the eastern and western regions, firms with low financing constraints, and those with high media attention. Further analysis shows that the EPTR has a positive impact on the green total factor productivity (GTFP) of enterprises, which implies that enterprises are not only proactively pushing for a green transformation at the strategic level but also taking practical actions. This study responds to the problem of the greening of tax system to promote the green development of enterprises from two aspects of enterprise strategic implementation and productivity and explores the impact mechanism from the perspective of institutional logic. It enriches the research on the effectiveness of the EPTR at the micro-level and broadens the research perspective on the impact mechanisms of environmental regulation. The findings of this study provide references for further optimising relevant policies and regulations and also offer insights for other countries and regions seeking sustainable development.

The brother's penalty: Boy preference and girls' health in rural China

This paper identifies the health penalty experienced by girls due to having a brother from endogenous sibling gender composition. We propose a girls-to-girls comparison strategy and rule out the confounding effect from the sibship size, birth interval, and birth order. Employing an instrumental variable approach and data from the Chinese Family Panel Studies, we find that girls with a brother are demonstrably shorter and report poorer health. This "brother's penalty" manifests even prenatally. Alternative explanations, such as birth order disadvantages, are carefully addressed and ruled out. The results hold even after excluding gender-neutral ethnic minorities. This observed penalty is likely attributed to unequal resource allocation within families and potential parental neglect. This penalty is amplified in families with lower income and maternal education, implying resource constraints contribute to gender discrimination. Our findings highlight the importance of addressing intrafamily gender bias for ensuring equal opportunities and health outcomes. Clinical trial registration: Not applicable.

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19)

BACKGROUND AND AIMS

The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion.

METHODS

We searched Baidu News using the keywords "Novel Coronavirus" and "COVID-19" from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data.

RESULTS

We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event.

CONCLUSIONS

The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

Saccadic targeting in the Landolt-C task: Implications for Chinese reading

Participants in an eye-movement experiment performed a modified version of the Landolt-C paradigm (Williams & Pollatsek, 2007) to determine if there are preferred viewing locations when they searched for target squares embedded in linear arrays of spatially contiguous clusters of squares (i.e., sequences of one to four squares having missing segments of variable size and orientation). The results of this experiment indicate that, although the peaks of the single- and first-of-multiple-fixation landing-site distributions were respectively located near the centers and beginnings of the clusters, thereby replicating previous patterns that have been interpreted as evidence for the default saccadic-targeting hypothesis, the same dissociation was evident on nonclusters (i.e., arbitrarily defined regions of analysis). Furthermore, properties of the clusters (e.g., character number and gap size) influenced fixation durations and forward saccade length, suggesting that ongoing stimulus processing affects decisions about when and where (i.e., how far) to move the eyes. Finally, results of simulations using simple oculomotor-based, default-targeting, and dynamic-adjustment models indicated that the latter performed better than the other two, suggesting that the dynamic-adjustment strategy likely reflects the basic perceptual and motor constraints shared by a variety of visual tasks, rather than being specific to Chinese reading. The theoretical implications of these results for existing and future accounts of eye-movement control are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas

Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situation of various provinces in ethnic minority areas has improved from 2012 to 2021, among which Tibet province is the most serious and Shaanxi is the best. According to the analysis of convergence, it was observed that there is no σ-convergence of multidimensional relative poverty in ethnic areas in general, and there is absolute β-convergence in general and in the southwest and northwest regions, and there is no absolute β-convergence in the northeast region. Based on this, policy recommendations for reducing multidimensional relative poverty are proposed at the end of the article. Compared with previous studies, this article focuses on ethnic regions that are easily overlooked. Starting from the dimensions of economy, social development, and ecological environment, the poverty measurement system has been enriched.

Longitudinal Associations Between Interpersonal Distrust and Social Aggression During College: Disentangling the Within-Person Process from Stable Between-Person Differences

There is a dearth of information on the relationship between interpersonal distrust and social aggression in the youth, although both may lead to negative interpersonal relationships. Furthermore, scholars have not explored whether interpersonal distrust influences later social aggression over time at the within-person level. This study used five wave longitudinal data to investigate the longitudinal association between interpersonal distrust and social aggression and the role of hostile attribution bias in this relationship; notably, it used a relatively rigorous approach-the random intercept cross-lagged panel model-to disentangle within-person processes from stable between-person differences. The final number of participants included 1053 undergraduate students (677 female students and 376 male students), and 64.3% were female students, with a mean age of 18.45 years (SD = 0.95) at first measurement. Participants completed assessments for interpersonal distrust, hostile attribution bias, and social aggression at five time points across 6-month intervals. At the within-person level, the results revealed that interpersonal distrust was a predictor of later social aggression and that hostile attribution bias acted as a longitudinal mediator in this relationship. This result indicates that to enhance interpersonal harmony and reduce individual hostility and aggression toward others, intervention programs should aim to reduce interpersonal distrust.

The research of river basin ecological compensation based on water emissions trading mechanism

By integrating the successful case of the European Union emissions trading system, this study proposes a water emissions trading system, a novel method of reducing water pollution. Assuming that upstream governments allocate initial quotas to upstream businesses as the compensation standard, this approach defines the foundational principles of market trading mechanisms and establishes a robust watershed ecological compensation model to address challenges in water pollution prevention. To be specific, the government establishes a reasonable initial quota for upstream enterprises, which can be used to limit the emissions of upstream pollution. When enterprises exceed their allocated emissions quota, they face financial penalties. Conversely, these emissions rights can be transformed into profitable assets by participating in the trading market as a form of ecological compensation. Numerical simulations demonstrate that various pollutant emissions from upstream businesses will have various effects on the profits of other businesses. Businesses in the upstream region received reimbursement from the assigned emission rights through the market mechanism, demonstrating that ecological compensation for the watershed can be achieved through the market mechanism. This novel market trading system aims at controlling emissions management from the perspectives of individual enterprises and ultimately optimizing the aquatic environment.

Enhancing environmental sustainability in transferred farmlands through rural e-commerce: insights from China

The issue of farmers neglecting environmental concerns in transferred farmlands poses a serious challenge, contradicting the long-term ecological goals of establishing resource-efficient and environment-friendly agriculture. Amidst the pivotal trend of moderately scaled agricultural operations, rural e-commerce holds promise as a catalyst and driving force for enhancing long-term environmental governance of transferred lands. The effectiveness and mechanisms of this potential, however, remain to be empirically examined. This study gathers panel data on environmental positive and negative externalities from six provinces in China, spanning the period from 2013 to 2022, encompassing 6372 farmers. A quasi-natural experiment of farmers' e-commerce participation is designed using difference-in-differences methodology (DID), propensity score matching (PSM), and moderating models. The primary findings are as follows: E-commerce participation increases farmers' positive environmental inputs on transferred lands, such as water-saving irrigation, adoption of social services, and preservation of traditional varieties. Simultaneously, it decreases negative environmental inputs, such as the consumption of fertilizers, pesticides, and agricultural films. The environmental sustainability effects of e-commerce vary across the eastern, central, and western regions of China. E-commerce has a more pronounced impact on agricultural social services and chemical pollutants in the eastern and central regions, while its influence is more significant on water-saving irrigation and variety preservation in the western region. Land transfer forms and supply order contracts do not directly promote farmers' environmentally friendly cultivation practices. Instead, they catalyze the environmental effects of e-commerce through a significant positive interaction term. These conclusions hold after matching for e-commerce participation propensity, while passing sensitivity tests, parallel trend tests, and placebo tests. Consequently, rural e-commerce, without compromising farmers' income, enhances the proactiveness of farmers in environmental conservation, transforms agricultural management practices, and effectively reduces rural non-point source pollution. Policy recommendations include reducing institutional barriers to rural e-commerce participation at the national level, encouraging the establishment of region-specific agricultural environmental sustainability goals, and leveraging the rural e-commerce industry chain to establish a nationwide environmental credit database and incentive mechanism.

Can green funds improve corporate environmental, social, and governance performance? Evidence from Chinese-listed companies

Green funds play pivotal roles in driving corporate sustainable development. Utilizing data from Chinese publicly listed companies from 2010 to 2021, we examine the impact of green funds on corporate environmental, social, and governance (ESG) performance and the underlying mechanisms. The research findings claim that green funds positively affect corporate ESG performance. Mechanism analysis systematically demonstrates that green funds contribute to elevated corporate ESG performance by alleviating financial constraints, enhancing managerial efficiency, and fostering green innovation. Heterogeneity analysis further underscores that the effect of green funds is particularly potent in companies with high external attention. Furthermore, green funds also play significant roles in production capabilities and economic value. This research enriches the micro-level evidence on the development of green funds and furnishes substantial implications for sustainable development.

Early warning on safety risk of highly aggregated tourist crowds based on VGGT-Count network model

In the era of mass tourism, more and more people are attracted by internet-famous site. With people's demand for travel surged, tourists are getting together in one scenic spot with doubling numbers, which easily leads to high concentration of tourists with uncontrollable security risks. It needs to be highly valued by the tourism department. Monitoring and issuing warnings for crowd density in scenic areas with Highly Aggregated Tourist Crowds (HATCs) is an urgent challenge that needs to be addressed. In this paper, Highly Aggregated Tourist Crowds is taken as the research objective, and a VGGT-Count network model is proposed to forecast the density of HATCs. The experimental outcomes demonstrated a substantial improvement in counting accuracy for the ShanghaiTech B and UCF-QNRF datasets. Furthermore, the model allows for real-time monitoring of tourist attractions, enabling advanced prediction of high concentrations in scenic areas. This timely information can alert relevant authorities to implement preventive measures such as crowd control and flow regulation, thereby minimizing safety hazards.

Evaluation of China's long-term care insurance policies

Introduction

In response to the increasing demand for long-term care services for older people, the Chinese government has launched a pilot program for long-term care insurance (LTCI) since 2016. The objective of this study is to evaluate the performance and effectiveness of this program in China and provide recommendations for the future development and expansion of the LTCI system.

Methods

We developed a comprehensive evaluation framework to assess these LTCI policies implemented in all 49 pilot cities in China.

Results

Based on our evaluation, the average assessment score for the LTCI program across all pilot cities was 71.8 points, with scores ranging from 57.5 to 92.5 points in these cities. Furthermore, most of the pilot cities achieved higher scores in the fact-based assessment compared to the value-based assessment.

Discussion

The results suggested that the overall pilot effect regarding LTCI was favorable, but there were significant regional disparities. Moreover, in most of pilot cities, current LTCI policies were designed to alleviate both the financial burden and the burden of caring for people with disabilities that families faced. However, some challenges still remained, such as the lack of community and home-based care services, the need to expand the coverage of insurance, and the importance of diversifying funding sources.

How to form shared objects to enhance university-school collaboration? A cultural-historical activity theory perspective

Introduction

University-school (U-S) collaboration has proven to be an effective approach for teacher professional development, but it could be hampered by the lack of shared objects. To understand how shared objects are formed in U-S collaboration, this research established a university-school collaborated Change Laboratory in W primary school based on cultural-historical activity theory, which is under the background of Chinese teaching research activity.

Methods

Recordings of meetings throughout the year were transcribed into texts and coded, and then analyzed via the method of grounded theory and contradiction analysis.

Results

The findings reveal that, in comparison to previous studies regarding shared object formation process, this study identified an special phase named "experimental object," which highlights the significance of experimentation in U-S collaboration. Also, multiple contradictions are recognized as the driving force for shared object formation which would gradually transform into fundamental conflicts between tools. The main contradictions identified include those between scientific and daily concepts, university culture and school culture, as well as new experiment and old routine.

Discussion

The current study implicates that U-S collaboration is an expansive learning process to acquire unknown knowledge, which necessitates both parties engaging in exploration and experimentation together. Furthermore, shared object formation within U-S collaboration requires participants to focus on developing teaching tools while consciously undergoing changes in aspects such as logic of thinking, culture and routine.

Evaluation of healthcare-related factors influencing mental health of Taiwanese citizens among different age groups

The issue of mental health has gained heightened recognition as a significant public health concern due to its potential to significantly impact various aspects of individuals' lives. Numerous factors may influence mental health, and this study seeks to investigate and compare potential healthcare-related factors that affect the mental health of Taiwanese individuals across different age groups. Data for this study were taken from the Taiwan Social Change Survey (TSCS), conducted in 2021. Descriptive statistics were calculated to compare the three age groups. Then, multiple regression models were constructed with mental health conditions as the dependent variable and demographics and other key healthcare-related components as independent variables, respectively. Results showed that, among the three age groups, the middle-aged adults had the highest BMI, and the older adults had significantly better mental health. As compared with the other age groups, the older adults had significantly better perceptions of fair distribution of healthcare resources, and their trust in the healthcare system was the highest. With regard to searching for online healthcare information, the frequency reported by the older adults was the lowest. The regression model showed that, religious belief, trust in the healthcare system and searching for online healthcare information were significantly associated with mental health of middle-aged adults. In the younger group, searching for online healthcare information was significantly negatively associated with mental health. The study's findings provide insight into how to provide Taiwanese citizens of different age groups with proper and targeted mental health promotion activities.

Toxicological responses of A549 and HCE-T cells exposed to fine particulate matter at the air-liquid interface

Fine particulate matter (PM2.5) can enter the human body in various ways and have adverse effects on human health. Human lungs and eyes are exposed to the air for a long time and are the first to be exposed to PM2.5. The "liquid immersion exposure method" has some limitations that prevent it from fully reflecting the toxic effects of particulate matter on the human body. In this study, the collected PM2.5 samples were chemically analyzed. An air-liquid interface (ALI) model with a high correlation to the in vivo environment was established based on human lung epithelial cells (A549) and immortalized human corneal epithelial cells (HCE-T). The VITROCELL Cloud 12 system was used to distribute PM2.5 on the cells evenly. After exposure for 6 h and 24 h, cell viability, apoptosis rate, reactive oxygen species (ROS) level, expression of inflammatory factors, and deoxyribonucleic acid (DNA) damage were measured. The results demonstrated significant dose- and time-dependent effects of PM2.5 on cell viability, cell apoptosis, ROS generation, and DNA damage at the ALI, while the inflammatory factors showed dose-dependent effects only. It should be noted that even short exposure to low doses of PM2.5 can cause cell DNA double-strand breaks and increased expression of γ-H2AX, indicating significant genotoxicity of PM2.5. Increased abundance of ROS in cells plays a crucial role in the cytotoxicity induced by PM2.5 exposure These findings emphasize the significant cellular damage and genotoxicity that may result from short-term exposure to low levels of PM2.5.

Corporate digital transformation, internal control and total factor productivity

Based on Resource-based theory and Internal Control (IC) theory, this study elucidates the impacts of corporate digital transformation on total factor productivity, and IC effectiveness, as well as the mechanism among digital transformation, IC and total factor productivity. The results show that digital transformation promotes total factor productivity and IC effectiveness. And effective IC has a significant mediating effect for the impact of digital transformation on total factor productivity. Heterogeneity discussion shows that compared with high-tech enterprises, in non-high-tech ones, digital transformation increases total factor productivity, and more significantly enhances IC effectiveness, presenting a mechanism that digital transformation facilitates IC, and increases total factor productivity. For non-high-tech enterprises, with higher heterogeneity of executive education backgrounds, digital transformation promotes IC effectiveness and total factor productivity, showing the transmission effect among digital transformation, IC and total factor productivity. Finally, it is suggested that the regulatory authorities advance digital infrastructure construction, to reinforce IC and risk prevention, thereby increase total factor productivity. And enterprises grasp the opportunity of digital economy development, promote the mechanism that digital transformation facilitates IC effectiveness, and increases total factor productivity. Non-high-tech ones motivate digital elements' governance efficacy, optimize executive structure, coordinately promote digital strategy, and help the national economy acquire high-quality development. The study provides enlightenments to achieve high-quality development.

Agricultural land management and rural financial development: coupling and coordinated relationship and temporal-spatial disparities in China

The integrated development of agricultural land and finance not only promotes rural financial innovation and breaks the bottleneck of agricultural financing but also facilitates agricultural land transfer and scaled operations. This leads to the advancement of the effective growth of contemporary agriculture. The reform of the 'separation of three rights' in agricultural land promotes land circulation, which, in turn, offers an institutional guarantee for the tandem development of rural finance and agricultural land management. This paper measures the comprehensive development index of agricultural land management and rural finance in 30 provinces of China from 2005 to 2020. In light of this, it calculates the degree of coupling and coordination between China's agricultural land management and rural financial development. The Dagum Gini coefficient, kernel density, and the Moran index were used to analyze regional differences and patterns of agglomeration. The study found that the degree of coupling coordination between China's agricultural land management and rural finance is increasing annually. However, there remains a significant gap in achieving high-quality coupling. Notably, the growth rate of rural financial development exceeds that of agricultural land management, and hypervariable density is a major source of regional variation. There is polarization in the coupled development of farmland management and rural finance. Provinces in the eastern and central regions tend to be located in the high-high agglomeration (H-H) in terms of the level of development of agricultural land and financial integration, while the western region tends to fall in low-low aggregation (L-L).

Industrial technology progress, digital finance development and corporate risk-taking: Evidence from China's listed firms

Industrial technological progress, as an essential industrial-technological and institutional phenomenon, brings with it the possibility of high profits for firms but also implies new norms and rules of competition, which affect the willingness and propensity of firms to bear the costs of undertaking venture capital projects. This study empirically investigates the causal impact of industrial-technological progress on corporate risk-taking and the mechanism of digital financial growth on the relationship between the two, based on data from China's A-share listed businesses from 2011 to 2020. This paper finds that (1) industrial technological progress improves enterprise risk-taking levels. Moreover, digital financial development has an incentive effect on industrial technological progress and enterprise risk-taking levels. (2) Industrial technological progress under digital financial development generates financing constraint relaxation effects, input capital return enhancement effects, and innovation performance incentive effects, increasing enterprise risk-taking. (3) The positive moderating effect of digital financial development on the relationship between industrial technological progress and the risk-taking level of enterprises in the eastern regions and enterprises in the high-tech industry is more prominent. The study's findings provide a theoretical foundation and policy insights on the crucial elements of industrial-technological progress and enterprises' increased ability to take risks throughout the development of digital finance.

Study on the impact of digital transformation on the innovation potential based on evidence from Chinese listed companies

Digital transformation has emerged as a powerful force in reshaping the business landscape and enabling organizations to enhance their capabilities. One critical aspect of this change is how it impacts an enterprise's innovation ability. To explore this question, we select data regarding China's A-share listed enterprises from 2007 to 2021 as the research sample. We employ crawler technology to gather keywords related to "digital transformation" from annual reports, portraying detailed journeys of enterprises' digital transformation. Through descriptive statistics and multiple covariance tests, a linear relationship is established between digital transformation and innovation ability. Benchmark regression is conducted and a robustness test is utilized to determine the robustness of the benchmark regression. The mechanism, heterogeneity, and moderating effects of this study are also tested. The results reveal that digital transformation makes a significant positive contribution to the innovation capability of enterprises. Meanwhile, among different types of enterprises, the impact of digital transformation on enterprise innovation capability shows heterogeneity. In terms of the impact mechanism, digital transformation can enhance the innovation output of enterprises by reducing the agency cost and improving the risk-taking level of enterprises, so as to further improve the innovation capability of enterprises. The research results of this paper provide essential theoretical support for the digital transformation of enterprises and the government's formulation of enterprises' digitalization strategies. More profoundly, it provides significant reference for how to further promote the digital transformation of Chinese enterprises.

Driving forces of digital transformation in chinese enterprises based on machine learning

With advanced science and digital technology, digital transformation has become an important way to promote the sustainable development of enterprises. However, the existing research only focuses on the linear relationship between a single characteristic and digital transformation. In this study, we select the data of Chinese A-share listed companies from 2010 to 2020, innovatively use the machine learning method and explore the differences in the predictive effects of multi-dimensional features on the digital transformation of enterprises based on the Technology-Organization-Environment (TOE) theory, thus identifying the main drivers affecting digital transformation and the fitting models with stronger predictive effect. The study found that: first, by comparing machine learning and traditional linear regression models, it is found that the prediction ability of ensemble earning method is generally higher than that of tradition measurement method. For the sample data selected in this research, XGBoost and LightGBM have strong explanatory ability and high prediction accuracy. Second, compared with the technical driving force and environmental driving force, the organizational driving force has a greater impact. Third, among these characteristics, equity concentration and executives' knowledge level in organizational dimension have the greatest impact on digital transformation. Therefore, enterprise managers should always pay attention to the decision-making role of equity concentration and executives' knowledge level. This study further enriches the literature on digital transformation in enterprises, expands the application of machine learning in economics, and provides a theoretical basis for enterprises to enhance digital transformation.

Sarcopenia among treated cancer patients before and after neoadjuvant chemotherapy: a systematic review and meta-analysis of high-quality studies

BACKGROUND

Neoadjuvant chemotherapy, used to shrink tumors before surgery, is increasingly applied in clinical practice. However, retrospective studies indicate that it may increase sarcopenia rates and consequently result in an elevated occurrence rate of postoperative severe complications such as severe surgical incision infection, severe respiratory failure, and severe postoperative hemorrhage, especially in the elderly population. Currently, no systematic analysis examines the association between neoadjuvant chemotherapy and sarcopenia. This study aims to fill this gap with a comprehensive meta-analysis focused on this critical aspect of the field.

METHODS

A systematic literature search was conducted in the PubMed and Web of Science databases from their inception to January 2024. The included studies encompassed patients who received neoadjuvant chemotherapy and underwent computed tomography (CT) scans both before and after treatment to calculate skeletal muscle index (SMI) or categorize them for the presence of sarcopenia. The determination of sarcopenia status was based on well-established and validated threshold criteria. Data extraction was performed independently by two reviewers. A meta-analysis was employed to estimate the pooled odds ratio (OR) and its corresponding 95% confidence interval (95% CI) to assess the risk of neoadjuvant chemotherapy-induced muscle reduction.

RESULTS

In the 14 studies with complete categorical variable data, comprising 1853 patients, 773 patients were identified as having sarcopenia before neoadjuvant treatment and 941 patients had sarcopenia after neoadjuvant therapy. The OR and its 95% CI was calculated as 1.51 [1.31, 1.73]. Among these, 719 patients had digestive system cancer, with 357 patients having sarcopenia before neoadjuvant treatment and 447 patients after, resulting in an OR of 1.74 [1.40, 2.17]. In the remaining 1134 patients with non-digestive system cancers, 416 were identified as having sarcopenia before neoadjuvant treatment, and 494 patients had sarcopenia after, with an OR of 1.37 [1.15, 1.63]. Additionally, in seven studies with complete continuous variable data, including 1228 patients, the mean difference in the change of SMI before and after neoadjuvant treatment was  - 1.13 [- 1.65,  - 0.62]. After excluding low-quality small-sample studies with fewer than 50 patients, the same trend was observed in the analysis.

CONCLUSION

The risk of muscle reduction significantly increases in cancer patients after neoadjuvant chemotherapy and digestive system cancers tend to have a higher risk of developing sarcopenia post-treatment compared to non-digestive system cancers.

Shared structure of fundamental human experience revealed by polysemy network of basic vocabularies across languages

How are concepts related to fundamental human experiences organized within the human mind? Our insights are drawn from a semantic network created using the Cross-Linguistic Database of Polysemous Basic Vocabulary, which focuses on a broad range of senses extracted from dictionary entries. The database covers 60 basic vocabularies in 61 languages, providing 11,841 senses from 3736 entries, revealing cross-linguistic semantic connections through automatically generated weighted semantic maps. The network comprises 2941 nodes connected by 3573 edges. The nodes representing body parts, motions, and features closely related to human experience occupy wide fields or serve as crucial bridges across semantic domains in the network. The polysemous network of basic vocabularies across languages represents a shared cognitive network of fundamental human experiences, as these semantic connections should be conceived as generally independent of any specific language and are driven by universal characteristics of the real world as perceived by the human mind. The database holds the potential to contribute to research aimed at unraveling the nature of cognitive proximity.

Peer Stress Spills Over to Family Stress in the Context of Emotion Regulation Difficulties: A Daily Diary Study with Chinese Adolescents

Conflict in peer and family relationships becomes more common in the adolescent period when compared to previous developmental periods. These typical developmental challenges can be exacerbated in the context of poor emotion regulation skills. Using daily diary data, the current study examined the stress spillover effects of peer and family stress on one another, as well as the moderating role of emotion regulation challenges (i.e., emotional inhibition, dysregulation). A sample of 310 Chinese adolescents (Mage = 13.02 years, SD = 0.76 years, 50.7% boys) completed an initial measure of emotion regulation difficulties, then reported on peer and family stress for 10 consecutive weekdays. Results indicated that there was an overall same-day peer stress spillover effect in which adolescents' peer stress on a given day was negatively associated with later conflictual interactions with their parents. Further, the relation between peer stress and same- and next-day family stress was exacerbated in the context of high levels of emotional inhibition. Family stress did not significantly relate to next-day peer stress, nor was this association moderated by difficulties with emotion regulation. These results highlight the temporal sequence of daily peer-to-family stress spillover. Though emotional inhibition may be culturally adaptive for maintaining interpersonal harmony, it can be maladaptive in managing stress for Chinese adolescents.

Impact of ecological presence in virtual reality tourism on enhancing tourists' environmentally responsible behavior

In an era where environmental conservation is increasingly critical, identifying pathways through which technological innovations like virtual reality tourism (VRT) can promote sustainable behaviors is vital. This study investigates the impact of 'ecological presence', a newly proposed sub-dimension of presence in VRT, on tourists' environmentally responsible behavior (TERB). Through structural equation modeling and fuzzy set qualitative comparative analysis of data from 290 participants, we unveil that ecological presence-defined as the authenticity and immersion of tourists in virtual ecological environments-significantly bolsters biospheric values, environmental self-identity, and personal norms. Additionally, our findings indicate that ecological presence in VRT indirectly promotes TERB, predominantly through the mediation of enhanced biospheric values and environmental self-identity. Notably, ecological presence, biospheric values, and environmental self-identity constitutes a sufficient condition for achieving a high level of TERB. This research highlights the potential of VRT as an innovative tool for tourism administrators to foster environmental stewardship, offering a novel approach to leveraging technology for conservation efforts.

ANGPTL3 is a novel HDL component that regulates HDL function

BACKGROUND

Angiopoietin-like protein 3 (ANGPTL3) is secreted by hepatocytes and inhibits lipoprotein lipase and endothelial lipase activity. Previous studies reported the correlation between plasma ANGPTL3 levels and high-density lipoprotein (HDL). Recently ANGPTL3 was found to preferentially bind to HDL in healthy human circulation. Here, we examined whether ANGPTL3, as a component of HDL, modulates HDL function and affects HDL other components in human and mice with non-diabetes or type 2 diabetes mellitus.

METHODS

HDL was isolated from the plasma of female non-diabetic subjects and type-2 diabetic mellitus (T2DM) patients. Immunoprecipitation, western blot, and ELISA assays were used to examine ANGPTL3 levels in HDL. Db/m and db/db mice, AAV virus mediated ANGPTL3 overexpression and knockdown models and ANGPTL3 knockout mice were used. The cholesterol efflux capacity induced by HDL was analyzed in macrophages preloaded with fluorescent cholesterol. The anti-inflammation capacity of HDL was assessed using flow cytometry to measure VCAM-1 and ICAM-1 expression levels in TNF-α-stimulated endothelial cells pretreated with HDL.

RESULTS

ANGPTL3 was found to bind to HDL and be a component of HDL in both non-diabetic subjects and T2DM patients. Flag-ANGPTL3 was found in the HDL of transgenic mice overexpressing Flag-ANGPTL3. ANGPLT3 of HDL was positively associated with cholesterol efflux in female non-diabetic controls (r = 0.4102, p = 0.0117) but not in female T2DM patients (r = - 0.1725, p = 0.3224). Lower ANGPTL3 levels of HDL were found in diabetic (db/db) mice compared to control (db/m) mice and were associated with reduced cholesterol efflux and inhibition of VCAM-1 and ICAM-1 expression in endothelial cells (p < 0.05 for all). Following AAV-mediated ANGPTL3 cDNA transfer in db/db mice, ANGPTL3 levels were found to be increased in HDL, and corresponded to increased cholesterol efflux and decreased ICAM-1 expression. In contrast, knockdown of ANGPTL3 levels in HDL by AAV-mediated shRNA transfer led to a reduction in HDL function (p < 0.05 for both). Plasma total cholesterol, total triglycerides, HDL-c, protein components of HDL and the cholesterol efflux function of HDL were lower in ANGPTL3-/- mice than ANGPTL3+/+ mice, suggesting that ANGPTL3 in HDL may regulate HDL function by disrupting the balance of protein components in HDL.

CONCLUSION

ANGPTL3 was identified as a component of HDL in humans and mice. ANGPTL3 of HDL regulated cholesterol efflux and the anti-inflammatory functions of HDL in T2DM mice. Both the protein components of HDL and cholesterol efflux capacity of HDL were decreased in ANGPTL3-/- mice. Our findings suggest that ANGPTL3 in HDL may regulate HDL function by disrupting the balance of protein components in HDL. Our study contributes to a more comprehensive understanding of the role of ANGPTL3 in lipid metabolism.

Examining the trajectory of meaning violation and its bidirectional relationship with perceived posttraumatic growth

Despite extensive theoretical discussions on the dynamic process of meaning violation (MV) and restoration, empirical research on this topic remained lacking. This study aimed to explore the trajectory of MV and the bi-directionality between MV and perceived posttraumatic growth (PPTG). This study employed a 3-wave longitudinal design spanning over 3 months, and a sample of participants from China who experienced any distressing event within the past 3 months was considered eligible. Participants (N = 215; aged 18-38 years old) were instructed to assess MV and PPTG regarding a chosen event. A latent growth model was used to examine changes in MV over time and a random intercept cross-lagged panel model was used to analyze bidirectional associations between MV and PPTG. Results revealed that, at the within-person level, MV at T1 negatively predicted PPTG at T2, while PPTG at T2 negatively predicted MV at T3. These results indicate that the sense of MV may have impeded PPTG in the initial stages, whereas PPTG might serve as a predictor for diminished MV at later stages. At the between-person level, a positive relationship between these two constructs was observed, suggesting that individuals who experienced higher levels of MV, in general, also tended to report greater PPTG. These findings reflect the complex and dynamic nature of meaning reconstruction processes and provide empirical evidence for the meaning-making model.

Impacts of chemical fertilizer reduction on grain yield: A case study of China

Reducing fertilizer usage is a crucial measure for achieving high-quality development in Chinese agriculture. Utilizing panel data from 31 Chinese provinces spanning from 2004 to 2019, this study empirically analyzes the dynamic relationship between fertilizer application and grain production, exploring the underlying mechanisms. The study findings reveal that the application of fertilizers maintains a positive impact on grain production. The two variables will demonstrate a dynamic alternation between "strong decoupling" and "retreat decoupling," suggesting that grain production may either increase or gradually decline, while fertilizer application exhibits a decreasing trend. Mechanism analysis reveals a distinct substitution relationship between fertilizer use efficiency and application quantity. Increasing fertilizer use efficiency while reducing application quantity still facilitates the stable and increased production of grains. Heterogeneity analysis indicates that the efficiency of fertilizer use has a more pronounced impact on grain yield in the eastern and western regions. Increasing fertilizer quantity is detrimental to wheat yield but has a promoting effect on corn yield. However, in the main grain-producing areas, increasing fertilizer quantity can enhance wheat yield but is unfavorable for the overall grain yield. Additionally, nitrogen fertilizer input has exceeded the optimal level compared to potassium fertilizer. Continuously increasing nitrogen fertilizer input will hinder the increase in grain yield. Therefore, there is a need to shift from the notion of "more fertilizer is better" and focus on improving fertilizer use efficiency to transition from the emphasis on "quantity" to "quality" of fertilizer application.

Why So Lonely? The Direct and Indirect Associations between Developmental Trajectories of Fear of Negative Evaluation, Prosocial Behavior and Loneliness in Adolescence

Fear of negative evaluation and prosocial behavior have been identified as predictive factors influencing the development of loneliness in adolescence, representing typical factors in the cognitive and behavioral processes of re-affiliation. The elucidation of plausible direct and indirect pathways linking these pivotal factors to adolescents' loneliness need further exploration. This study aimed to investigate the direct and indirect relationships between the fear of negative evaluation, prosocial behavior, and adolescents' loneliness through the lens of developmental changes. A total of 533 adolescents (49.0% girls, Mage = 15.18 years, SD = 0.71) participated in this longitudinal study, assessed at three timepoints over a span of two years with 12-month intervals. Latent growth modeling uncovered direct associations between the developmental trajectories of both fear of negative evaluation and prosocial behavior with the developmental trajectory of adolescents' loneliness. The developmental trajectory of fear of negative evaluation exhibited an indirect association with the developmental trajectory of loneliness through the mediating role of prosocial behavior. These findings highlighted the roles of cognitive and behavioral re-affiliation processes, both independently and as mediators, in influencing adolescent loneliness, suggesting that interventions aimed at reducing fear of negative evaluation and promoting prosocial behavior could effectively mitigate adolescents' loneliness.

The impact of digital transformation on enterprise performance: An empirical analysis based on China's manufacturing export enterprises

Currently, countries worldwide are embracing digital strategies, enabling enterprises to utilize digital technology, digital supply chains, blockchain, and additional digital measures to increase their competitiveness. This paper analyzed the correlation between the digital transformation of manufacturing export enterprises and their business and export performance, focusing on China's manufacturing export enterprises through empirical analysis. The study investigated the influence of digital transformation on enterprise performance. Using the Resource Based View theory and Trade theory, hypotheses were proposed and regression models were developed to analyze a sample of 1007 enterprises listed on the Shanghai and Shenzhen Stock markets from 2012 to 2019. The study conducted regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis. The study found that (1) Manufacturing export enterprises listed in the stock market implemented digital transformation, leading to a significant positive impact on their overall performance. (2) Digital transformation led to cost reduction, improved R&D intensity, and enhanced human resources, among other benefits for enterprise performance. (3) According to the fractal analysis, non-state-owned enterprises exhibited more favorable effects on enterprise performance, and the digital transformation of manufacturing export companies in developed regions had a more significant impact on their performance. Finally, the study's empirical results yielded pertinent proposals for digital transformation.

The Effect of Syntactic Similarity on Intra-Sentential Switching Costs: Evidence from Chinese-English Bilinguals

In order to better understand the role of syntactic similarity in a code-switched sentence, the current study explored the effect of similar and different syntactic structures on Chinese-English bilinguals' intra-sentential switching costs. L2 proficiency and switching directions as factors that potentially intervene in bilingual performance were together explored to see if there was any interaction. We manipulated the degree of syntactic similarity by utilizing clauses in active voice (greater similarity) and passive voice (lesser similarity). The study conducted a self-paced reading paradigm as a more natural language reading processing. Results showed overall longer reading times for active sentences than passive counterparts, which supported a syntactic similarity impediment rather than facilitation. The impediment seemed to be predominant irrespective of L2 proficiency. Furthermore, syntactic similarity modulated the asymmetry of switching costs between forward (L1-L2) and backward (L2-L1) direction: word RTs for the 1st and the 2nd switched word yielded greater costs in L2-L1 condition, while greater costs in L1-L2 condition was observed in 3rd switched word RTs and average RTs. The present study observed syntactic similarity impediment rather than facilitation for Chinese-English bilinguals. Notably, syntactic similarity plays a predominant role compared to L2 proficiency, and modulates the asymmetry between switching directions.

Screening of sustainable supply chain performance evaluation indicators based on the ill-conditioned index cycle method

The establishment of an evaluation indicator system that can accurately assess the sustainability of a supply chain while further enhancing its performance is vital and relevant. Based on the connotation of sustainable supply chains and triple bottom line theory, indicators are initially proposed from economic, environmental, and social dimensions. To increase the explanatory power of the indicator system and decrease information redundancy, the coefficient of variation is applied to identify the indicators with weak interpretation intensity, the ill-conditioned index cycle method is utilized to filter out indicators with redundant information, and data on 100 Chinese listed companies from 2019 to 2021 are used as samples. A performance evaluation indicator system of sustainable supply chains with 16 indicators is ultimately established. The information interpretation strength index and cumulative information contribution rate verify the rationality of the final indicator system. The outcome demonstrates that this screening method can strengthen the representativeness of the indicator system and rapidly reduce redundancy, leading to the better discrimination of the evaluation results. The findings of this study provide an indicator system and a methodological reference for both companies and policymakers and can aid in the transformation of supply chains toward sustainability.

Factors affecting the protection of data rights in sports events: a configurational analysis

The development of algorithms and the spread of digital infrastructure have contributed significantly to the productivity of the digital economy. Data has come to be known as the "oil of the digital economy". At the same time, data has begun to participate more deeply in the production activities of the global sports industry chain, and the international discussion on how to protect the rights of sports event data has been increasing. Based on the configurational theory and fuzzy-set qualitative comparative analysis, this study discusses the factors affecting the protection of sports event data rights. The study found three configuration paths for achieving high enterprise data protection effectiveness and two for achieving low enterprise data protection effectiveness. The results of this study provide theoretical support for governments to address the issue of sports event data rights. They will also facilitate the safe use of data in sports, promote the global sports industry and humanitarian action development, and contribute to international sustainable development.

A dynamic panel threshold model analysis on heterogeneous environmental regulation, R&D investment, and enterprise green total factor productivity

Environmental regulations are important means to influence manufacturing enterprise green development. However, there are two completely different conclusions both in theoretical and in empirical research, namely the "Follow Cost" theory and the "Porter Hypothesis". The nonlinear mechanism needs to be considered. Therefore, this study aims to explain the threshold impact of heterogeneous environmental regulations on enterprise green total factor productivity. Environmental regulations are divided into different sub-categories, then based on the panel data of 1220 Chinese manufacturing listed companies from 2011 to 2020, this paper uses threshold regression model to examine the impact of heterogeneous environmental regulations on Chinese manufacturing enterprise Green Total Factor Productivity. The empirical results show that: (1) Command-controlled, market-incentive and voluntary-agreement environmental regulation all have a significant nonlinear impact on enterprise Green Total Factor Productivity. (2) Enterprise R&D investment plays a threshold role in the impact. (3) There are industry and equity type differences in the impact process. This study focuses on the micro level of enterprises and tests the threshold mechanism, which make some theoretical complement to previous researches. The research results are not only beneficial for the government to propose appropriate environmental regulatory policies, but also for enterprises to achieve green growth through heterogeneous R&D investment.

The effects of dietary diversity on health status among the older adults: an empirical study from China

BACKGROUND

Dietary diversity is an indicator of nutrient intake among the elderly. Previous researches have primarily examined dietary diversity and the risks with chronic and infectious disease and cognitive impairment, limited evidence shows the association between dietary diversity and the overall health status of specific populations with a heterogeneity analysis. This study aimed to probe the effects of dietary diversity on health status among Chinese older adults.

METHODS

There were 5740 sample participants aged 65 and above selected from the Chinese Longitudinal Healthy Longevity Survey, among which 3334 samples in 2018 wave and 2406 samples in 2011 wave. Dietary diversity was assessed by Dietary Diversity Score ranged from 0 to 9, the higher the score, the better dietary diversity. Health status was assessed into healthy, impaired and dysfunctional state by three indicators: Activities of Daily Living, Instrument Activities of Daily Living and Mini-Mental State Examination. Multinomial logistic regression was employed to assess the effects of dietary diversity on the health status among the elderly. Heterogeneity analysis between different groups by age was further discussed.

RESULTS

Older adults with better dietary diversity are in better health status, the mean dietary diversity score for healthy group was higher than that of impaired and dysfunctional groups (In 2018 wave, the scores were 6.54, 6.26 and 5.92, respectively; and in 2011 wave, they were 6.38, 5.93 and 5.71, respectively). Heterogeneity analysis shows that the younger groups tend to have more diversified dietary and be in better health status. Dietary diversity was more significantly associated with health status of the younger elderly (OR, 1.22, 95% CI, 1.04-1.44, p < 0.05) than the older elderly (OR, 1.01, 95% CI, 0.37-2.78, p > 0.05) in 2018 wave; and in 2011 wave, dietary diversity was more significantly related to health status among the younger elderly (OR, 1.62, 95% CI, 1.26-2.08, p < 0.001) than the older elderly (OR, 0.08, 95%CI, 0.31-1.94, p > 0.05).

CONCLUSIONS

Better dietary diversity has positive effects on health status and is more significantly related to the younger elderly than the older elderly. So interventions including available dietary diversity assessment, variety of dietary assistance services in daily life, keeping nutrient digestion and absorption capacity for the venerable age might benefit to ensure the effects of dietary diversity on health status among older adults especially in maintaining intrinsic ability and physical function. In addition, healthy lifestyle should also be recommended.

Auditory language comprehension among children and adolescents with autism spectrum disorder: An ALE meta-analysis of fMRI studies

Difficulties in auditory language comprehension are common among children and adolescents with autism spectrum disorder. However, findings regarding the underlying neural mechanisms remain mixed, and few studies have systematically explored the overall patterns of these findings. Therefore, this study aims to systematically review and meta-analyze the functional magnetic resonance imaging evidence of neural activation patterns while engaging in auditory language comprehension tasks among children and adolescents with autism. Using activation likelihood estimation, we conducted a series of meta-analyses to investigate neural activation patterns during auditory language comprehension tasks compared to baseline conditions in autism and non-autism groups and compared the activation patterns of the groups, respectively. Eight studies were included in the within-group analyses, and seven were included in the between-group analysis. The within-group analyses revealed that the bilateral superior temporal gyrus was activated during auditory language comprehension tasks in both groups, whereas the left superior frontal gyrus and dorsal medial prefrontal cortex were activated only in the non-autism group. Furthermore, the between-group analysis showed that children and adolescents with autism, compared to those without autism, showed reduced activation in the right superior temporal gyrus, left middle temporal gyrus, and insula, whereas the autism group did not show increased activation in any of the regions relative to the non-autism group. Overall, these findings contribute to our understanding of the potential neural mechanisms underlying difficulties in auditory language comprehension in children and adolescents with autism and provide practical implications for early screening and language-related interventions for children and adolescents with autism.

Multi-attribute decision making based on VIKOR with probabilistic linguistic term sets: An application to the risk evaluation of foreign direct investment

The multiple global environments have triggered changes in the international environment, leading to a sharp decline of foreign direct investment (FDI) compared to pre-pandemic level. To evaluate the investment risk of FDI and make optimal investment decision becomes the most important issue for investors. This paper focuses on the evaluation of investment risk for FDI. First, an index system for risk evaluation of FDI is constructed. Then, we introduce the probabilistic linguistic entropy and cross entropy measures, based on which, a programming model is developed to identify the objective attribute weights. A composite weight derivation method, which takes both the objective attribute weights and the subjective attribute weights into account, is further introduced. In view of attributes' uncertainty and fuzziness and the conflicting characteristics of some attributes, the VIKOR (the Serbian name: VlseKriterijumska Optimizacija I Kompromisno Resenje, means multi-criteria optimization and compromise solution) method is used to evaluate the risk of FDI under the probabilistic linguistic environment. Furthermore, a case study is presented to illustrate the proposed method. The comparative analysis and some further discussions verify the validity of the proposed method for the FDI risk evaluation.

The impact of the EU's Carbon Border Adjustment Mechanism on the global iron and steel trade and emission reduction

The European Council completed the legislative procedure to establish the Carbon Border Adjustment Mechanism (CBAM) on April 25, 2023, which will be launched in 2027. The iron and steel sector is the main target of the forthcoming CBAM due to the industry's energy-intensive consumption with high carbon dioxide (CO2) emissions. However, minimal existing research has been conducted in this regard. This study employs GTAP-e 11.0 and TOPSIS models to estimate the effects of CBAM implementation on the major nations around the world from 2027 to 2030, examining countries' GDP, social welfare, iron and steel production, trade balance, and CO2 emissions to the global environment. This study concludes: (1) The GDP and social welfare of important iron and steel trade partners throughout the world will be significantly impacted by the application of CBAM. Most nations, including those in the EU, will experience negative GDP effects, with China undergoing the most pronounced social welfare declines followed by India. In contrast, the EU27 will benefit the most in terms of social welfare, followed by the US, Japan, and Russia. (2) Iron and steel production will decrease in all countries outside the EU, but it will have a positive impact on the trade balance of most countries. (3) The CO2 emissions of all countries except for the EU and Japan will decrease, with a positive impact on preventing carbon leakage in the international iron and steel trade. (4) Comprehensive analysis demonstrates that the EU will benefit the most, and China will suffer the most from CBAM application. Based on the above conclusions, this study proposes corresponding policy recommendations.