Public transportation is important for older adults to meet their mobility needs and obtain external support. However, little is known about the elderly population with disabilities using public transportation. Using a nationally representative sample from the China Family Panel Studies (CFPS) for 2016, 2018, and 2020, we examined the elderly and public transportation disability (E&PTD) rate and its determinants in Chinese adults aged 45 years and above; the E&PTD rate in this population was 9.65%. The results showed that factors such as being female, age, and family size increased the likelihood of E&PTD in older adults. Married older adults with more education, better intelligence, higher incomes, receiving a pension, and living in urban areas and pilot provinces of healthcare reform were less likely to have E&PTD. This study provides an important policy reference for providing better public transportation services for E&PTDs.
Advanced oxidation processes (AOPs) have a broad range of potential applications in the treatment of emerging refractory emerging pollutants. However, due to the presence of highly reactive substances such as free radicals that are difficult to capture, it is challenging to investigate the mechanism of AOPs at the elementary reaction level. The conventional methods, such as electron spin resonance (ESR), free radical quantification, and free radical quenching, are plagued by systematic issues that have led to bottlenecks in the field of AOP studies. The development of computational chemistry theory and computer performance provides a new method to study the mechanism of AOPs through density functional theory (DFT) calculation. Due to its excellent cost–performance benefit, DFT calculations for aperiodic small molecules have become popular in the field of AOPs. In this paper, a comprehensive review is presented on the applications of DFT calculations for predicting active sites and exploring reaction selectivity and oxidant activation mechanisms. A systematic classification of methods related to molecular descriptors and transition states is provided. Furthermore, some current research issues are identified, and future development prospects and challenges are discussed.
Persistent green innovation helps enterprises save energy, reduce pollution, and continue to gain economic benefits. However, existing studies explored the economic and organizational factors influencing firms’ persistent green innovation while neglecting peer influence in the digital economy. This study examines the impact of digital economy and peer influence on persistent green innovation using data of Chinese-listed companies from 2011 to 2019. The results show that digital economy and peer influence positively affect persistent green innovation. Moreover, digital economy plays a competitive mediating role between peer influence and persistent green innovation. The results of further research show that both the time lag term of peer influence and spatial lag term of digital economy affect persistent green innovation. This study incorporates the three-level elements of enterprise, peer, and city into a unified framework, providing theoretical reference and practical guidance for green innovation to enhance the competitive advantage of enterprises.
There is growing interest in the relationship between digitalization and environmental, social, and governance (ESG) performance, but existing research focuses on the one-way relationship and ignores the two-way mechanism. Based on a sample of 3335 listed companies in China in 2020, this study adopts a spatial simultaneous equation model to investigate the bidirectional mechanism between companies’ digitalization and ESG performance. The results show that digitalization and ESG performance have a significant positive two-way mechanism; digitalization enhances ESG performance, while ESG performance promotes digitalization. The results also indicate a significant positive intra-industry spillover effect for both digitization and ESG performance. Further research shows that the relationship between digitization and ESG performance does not differ depending on the definition of spatial weights, however, the spillover effects do differ depending on the definition of spatial weights.
Plastisphere, characterized by microbial colonization on plastic debris, has attracted concern with its adverse environmental effects. The microbial features have been increasingly investigated; however, there lacks direct evidence for microplastics serving as carbon sources and enriching plastic-degrading microorganisms. Here, we obtained microbial communities from soil microplastics, analyzed the dissimilarity compared with soil, and characterized the plastic-degrading potential of isolates from plastisphere. Results showed the plastisphere communities significantly differed from soil communities and exhibited a higher relative abundance of Nocardia and Rhodococcus. To verify the selective enrichment of plastic-degrading microorganisms in the plastisphere, culture-based strategies were employed to evaluate the polyethylene (PE) degradation potential of two isolates Nocardia asteroides No.11 and Rhodococcus hoagii No.17. They could grow solely on PE and led to significant weight loss. FTIR and SEM analysis revealed the formation of new functional groups and the destruction of structural integrity on PE surfaces. Genes related to PE biodegradation were identified by genome-wide sequencing thus recognizing relevant enzymes and elucidating potential pathways. Overall, this report combined culture-free and culture-based approaches to confirm the plastic degradation potential of selectively enriched microorganisms in soil plastisphere, providing a positive perspective toward promoting microplastic biodegradation in farmland soil by enhancing natural microbial processes.
Microplastics, recognized as some of the most pervasive and enduring pollutants, have emerged as a potential threat to environmental eco-health. While much is known about the effects of microplastics on soil microorganisms, our understanding of how they interact with terrestrial organisms and the underlying mechanisms remains limited. In this study, the effects of polyethylene microplastics at a concentration of 0.5 % (w/w) on the antioxidant enzymes, gut microbiota of Eisenia fetida and the soil microbiota on days 1, 3, 7, 15, and 30 were investigated. The results indicated that exposure to microplastics slightly increased the activities of superoxide dismutase (1.22-fold on day 3, 1.12-fold on day 7) and catalase (1.10-fold on day 3, 1.09-fold on day 7) in E. fetida, while exposure markedly decreased peroxidase activity (1.33- to 1.79-fold) throughout the whole period. Both the soil microbiota and the gut microbiota of E. fetida in terms of diversity and composition were significantly affected by the microplastic amendment, and their structure tended to be similar throughout the exposure time. The family Nocardiaceae was significantly enriched in both the soil and E. fetida gut biota with microplastic exposure. Our results demonstrated that the antioxidant enzyme response of E. fetida was closely related to both the microbiota, although this relationship with the gut microbiota may have been weakened by microplastic exposure. Overall, this study furnishes new perspectives on the ecotoxicity of microplastics, revealing significant implications for the vitality of soil-dwelling organisms and the overarching health of terrestrial ecosystems.
The multiple-channel[1] sound source enhancement methods have made a great progress in recent years, especially when combined with the learning-based algorithms. However, the performance of these techniques is limited by the completeness of the training dataset, which may degrade in mismatched environments. In this paper, we propose a reconstruction Model based Self-supervised Learning (RMSL) method for sound source enhancement. A reconstruction module is used to integrate the estimated target signal and noise components to regenerate the multi-channel mixed signals, and it is connected with a separating model to form a closed loop.In this case, the optimization of the separation model can be achieved by continuously iterating the separation-reconstruction process. We use the separation error, the reconstruction error, and the signal-noise independence error as lossfunctions in the self-supervised learning process. This method is applied to the state-of-the-art sound source separation model (ADL-MVDR) and evaluated under different scenarios. Experimental results demonstrate that the proposed method can improve the performance of ADL-MVDR algorithm under different number of sound sources, bringing about 0.5 dB to 1 dB Si-SNR gain, while maintaining good clarity and intelligibility in practical application.
A visa-free policy is a tool for attracting foreign tourists, but existing studies evaluating its effects do not consider spatial spillover. This study, therefore, examined the effects of visa policies on urban inbound tourism with spatial spillover. This study used the implementation of the 72-hr visa-free transit policy in China as a natural experiment and employed a spatial difference-in-differences approach. The results show that the implementation of the 72-hr visa-free transit policy had no significant effect on the number of foreign tourists, but can reduce the average length of stay for foreign tourists. It also shows that there is a significant spatial spillover effect on the flow of foreign tourists. The results indicate the importance of spatial spillover in the evaluation of the impact of visa policy on inbound tourism, providing empirical evidence for further improving visa-free policies and urban tourism development.
Mega-events such as the Olympic Games, the World Cup, the World Expos, and the G20 Summit play important roles in international political economy in the age of globalization. But we know little about how they shape domestic politics and policy processes in their host countries. China has emerged as the leading host of various sports, cultural, economic, and political mega-events in the past decades. Employing an original panel dataset of Chinese cities from 2001 to 2019, we find that cities that host mega-events gain an advantage in bargaining with central bureaucracies for policy resources. Using subway investments as an example, we demonstrate that host cities not only obtained centrally regulated infrastructure investments that directly serve the needs of the events, but also achieve development that they otherwise could not. The result is robust with two-way fixed effects models and after accounting for various alternative explanations. We show that host cities gain advantage because the events capture the attention of national leaders. National leaders have power over central bureaucrats’ careers and thus steer their decisions, and they see the success of mega-events as an opportunity to project national strengths. Our findings highlight the domestic policy consequences of international events in the age of China’s rapid rise and integration with the world.
Populism has recently enjoyed success in Europe, the US, and beyond. Populist leaders and their supporters have accused “mainstream” media of being part of a “corrupt” elite that misrepresents the will of the virtuous “people.” Distrust of the media has also prompted the rejection of traditional media sources for political information and given prominence to alternative and hyperpartisan sources such as Breitbart. However, limited research exists concerning who consumes hyperpartisan media, how the websites of hyperpartisan media are interconnected, and what content is presented in hyperpartisan news. By combining cross-national surveys with large-scale digital trace datasets of website visits, this paper demonstrates the link between populist party support and hyperpartisan media visits. It also identifies influential sources of hyperpartisan news by analyzing the audience similarity networks of these websites and reveals country-level variations in hyperpartisan news and the dominance of US politics among the identified hyperpartisan news topics.
Financial inclusion and energy poverty have an interactive relationship; however, this two-way relationship lacks sufficient research. This study investigates the two-way mechanisms of financial inclusion, energy poverty, and neighborhood spillover effects. Using a spatial simultaneous equation model, this study examines 2615 Chinese rural households in 2020. Results reveal a statistically significant positive interaction between financial inclusion and energy poverty. In addition, the neighborhood spillover effects of financial inclusion and energy poverty are both significantly positive, whereas their neighborhood interaction spillover effects are significantly negative.
Using 13,584 observations of 4772 undergraduate students enrolled in 523 online classes offered synchronously at a research university in China, and using online-learning platform data and administrative data, this paper examines the impacts of class attendance on academic performance. Based on student-level and course-level fixed effects models with a unique set of student-course level control variables, this paper finds class attendance to have a significantly positive impact on academic performance. This effect is larger for low-performing students and smaller for students in courses with larger class sizes. The above findings survive a number of robustness checks, including a bounding technique, restricting sample to compulsory courses and limiting variation in attendance caused by whole day absence.