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The global digital wave has flourished in recent years, and the digital technology revolution has emerged. Digitalization plays an undeniable role in promoting modern economic and social development in multiple aspects such as economy, society, innovation, public services and sustainable development, China's digitalization application is also developing rapidly. In order to better measure the current situation of China's digitalization development level, this paper constructs a comprehensive evaluation index system of digitalization development from four dimensions of talents in the digital field, digital infrastructure construction, digitalization innovation ability and international competitiveness, and tests the index system. The entropy method is used to measure the level of digitalization development between China and the United States, the United Kingdom, France and other major developed countries in the world, and the coefficient of variation method, kernel density estimation and Dagum Gini coefficient method are used to analyze the temporal and spatial characteristics and regional differences of digitalization development level of seven countries. This paper makes a comparative analysis between China and major developed countries from the historical perspective of the evolution of the techno-economic paradigm. With a view to summarizing and exploring from it and drawing on the advanced experiences accumulated by the developed countries over a long period of time, so as to provide China with useful insights and bases for further enhancing its digitalization development level. [ABSTRACT FROM AUTHOR]

Bridge influence lines (BILs) and bridge influence surfaces (BISs) are inherent static parameters of bridges which can be extracted from moving vehicle-induced bridge responses. Compared with dynamic parameters, these parameters are directly related to the stiffness and internal forces in each cross-section of a bridge therefore can be considered as an effective bridge metamodel. To accelerate the engineering practice of BIL- and BIS-based bridge evaluation, this paper first briefly reviews the current BIL and BIS field test and identification methods. Then, the bridge evaluation guidelines of China and the United States are introduced as the basis of the evaluation methods. Engineering application scenarios for bridge evaluation, including permit load verification, performance degradation checking, and load carrying capacity evaluation, are summarized, and a multiple-scenario bridge evaluation method is established. At the end of this paper, an evaluation example of a four-span continuous bridge is presented to illustrate the application procedure and verify the effectiveness of the proposed method. The outcomes of this paper provide a promising application method of field test BILs and BISs, which may help bridge engineers more effectively use these parameters in engineering practice. [ABSTRACT FROM AUTHOR]

This paper critically examines China's national security review regime of foreign investment and compares it with that of the United States. Over the years, China has gradually established a comprehensive legal framework for national security review of foreign investment. Recent efforts were made to refine the public enforcement mechanism of the review in tandem with a new "pre-establishment national treatment plus negative list" system under the 2020 Foreign Investment Law. The United States also enacted the Foreign Investment Risk Review Modernization Act of 2018 to enhance its national security review regime. By analyzing the law and practices of China and the United States, this paper finds that the national security review regimes of the two jurisdictions have functional convergences despite some formal divergences caused by diverse political-economy landscapes. Their functional convergences are highlighted by China's local practices, such as the de-facto national security screening in the name of anti-monopoly review. There are many factors affecting China's national security review regime for foreign investment, including the ongoing (and escalating) US-China competition (or conflict) at the international level and the evolution of state or party capitalism at the domestic level. These research findings will not only contribute to the existing comparative law scholarship but also benefit multinational enterprises that seek to enter Chinese and the US markets. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) in the field of spinal cord injury (SCI) have garnered significant attention for their potential applications in diagnosis and therapy. However, no bibliometric assessment has been conducted to evaluate the scientific progress in this area. A search of articles in Web of Science (WoS) from January 1, 1991, to May 1, 2023, yielded 359 papers that were analyzed using various online analysis tools. These articles have been cited 10,842 times with 30.2 times per paper. The number of publications experienced explosive growth starting in 2015. China and the United States led this research initiative. Keywords were divided into 3 clusters, including "Pathophysiology of SCI", "Bioactive components of EVs", and "Therapeutic effects of EVs in SCI". By integrating the average appearing year (AAY) of keywords in VoSviewer with the time zone map of the Citation Explosion in CiteSpace, the focal point of research has undergone a transformative shift. The emphasis has moved away from pathophysiological factors such as "axon", "vesicle", and "glial cell" to more mechanistic and applied domains such as "activation", "pathways", "hydrogels" and "therapy". In conclusions, institutions are expected to allocate more resources towards EVs-loaded hydrogel therapy and the utilization of innovative materials for injury mitigation. [ABSTRACT FROM AUTHOR]

The rapid growth of China's national resources in the space domain may change the gap in power between China and the United States in relevant international rulemaking. This article proposes an analytical framework for identifying, comparing, and analyzing states' power resources critical to international rulemaking and uses the framework to compare the relevant resources between China and the United States in the space domain. First, this paper develops a method for identifying resources crucial to international rulemaking in outer space. The relevant resources of the two countries are then compared in this article. Finally, the article explores comparative advantages, consensus, differences, and cooperation possibilities of the two countries in specific international space rules. The framework could be adapted to compare diverse nations' resources critical to international rulemaking in other fields; it contributes to research on space law, international legislation, and national power. [ABSTRACT FROM AUTHOR]

The US global leadership in science and technology has greatly benefitted from immigrants from other countries, most notably from China in the recent decades. However, feeling the pressure of potential federal investigations since the 2018 launch of the China Initiative, scientists of Chinese descent in the United States now face higher incentives to leave the United States and lower incentives to apply for federal grants. Analyzing data pertaining to institutional affiliations of more than 200 million scientific papers, we find a steady increase in the return migration of scientists of Chinese descent from the United States to China. We also conducted a survey of scientists of Chinese descent employed by US universities in tenured or tenure- track positions (n = 1,304), with results revealing general feelings of fear and anxiety that lead them to consider leaving the United States and/or stop applying for federal grants. If the situation is not corrected, American science will likely suffer the loss of scientific talent to China and other countries. [ABSTRACT FROM AUTHOR]

Even though Sino-American relations of the Donald Trump era were perceived as predominately confrontational, with a symbolic trade war between the two, the scale of economic interdependencies between the United States and China results in either a need for collaboration or in serious losses on both sides in the case of lack of cooperation. The paper aims at analyzing economic relations between the United States of America and the People's Republic of China at the time of the Trump presidency. Analysis is based on the complex interdependence theory of Robert Keohane and Joseph Nye. The main hypothesis analyzed in the paper states: Asymmetric interdependence between the People's Republic of China and the United States of America limits the scope, intensity and length of a trade war. For the sake of the paper, economic interdependence will be analyzed. Apart from the reference to the state of the art, the document analysis and descriptive statistics are to be applied in the paper. [ABSTRACT FROM AUTHOR]

In this paper, we study long-term trends in social mobility in the People's Republic of China since its inception in 1949, with two operationalizations: 1) intergenerational occupational mobility and 2) intergenerational educational mobility. We draw on an accumulation of administrative and survey data and provide comparable estimates of these measures for birth cohorts born after 1945. To help interpret the results, we compare trends in China to those in the United States for the same birth cohorts. We find an increase in intergenerational occupational mobility in China due to its rapid industrialization in recent decades. Net of industrialization, however, intergenerational occupational mobility has been declining for recent cohorts. Intergenerational educational mobility in China shows a similar declining trend. In addition, mobility patterns have differed greatly by gender, with women in earlier cohorts and from a rural origin particularly disadvantaged. We attribute the general decline in social mobility to market forces that have taken hold since China's economic reform that began in 1978. In contrast, social mobility by both measures has been relatively stable in the United States. However, while social mobility in China has trended downward, it is still higher than that in the United States, except for women's educational mobility. [ABSTRACT FROM AUTHOR]

Using machine learning coupled with stock price data to predict stock price trends has attracted increasing attention from data mining and machine learning communities. An accurate prediction results can help investors reduce investment risks and improve investment returns. The research on correlation stocks is one of the most important directions among many studies. Due to the high volatility and randomness of stock data, the correlation between stocks changes over time, which makes the stock correlation in static correlation stock sets often inconsistent with reality. Furthermore, various raw data related to stocks contain sufficient stock history information to analyze the future trend of stocks, but traditional prediction models cannot make good use of this information, which restricts the learning ability of the model and reduces the prediction accuracy. In this paper, we propose a stock prediction model combining multi-view stock data features with dynamic market correlation information (MDF-DMC). The model extracts stock trend features by combining multi-view raw data of a single stock with a Multi-layer Perceptron Mixer (MLP-Mixer); The improved Transformer encoder learns the correlation between the stock to be predicted and all the selected stocks in the stock market dynamically and extracts the features of the market correlation. We have conducted a large number of experiments on a total of 578 stocks in the stock markets of China and the United States, and the results show that our model has achieved excellent accuracy and returns across all data sets. • Stock movements are influenced by both itself and the market. • Stock multidimensional data can be used to improve the forecasting performance. • The attention mechanism can effectively extract the correlation of market dynamics. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the risks of an over-concentration of supply chains in one country. It has motivated stakeholders to pursue diversification strategies. However, a paradox exists. Stakeholders have shied away from a complete decoupling and preferring to selectively enhance economic ties with China. This article explores this paradox by examining supply chain concentration in China as a form of asymmetric interdependence and the countermeasures from the U.S., Japan, Australia, and India to minimize vulnerabilities. It argues that while the COVID-19 disruptions have brought to light the risk of supply chain overconcentration in China, countermeasures are also driven by coercive diplomacy and the deepening U.S.-China rivalry. The paper also examines the feasibility of diversification efforts by focusing on the capacity and capabilities of alternative supply chain hubs. It finds that while states are actively seeking ways to prevent China from using asymmetric interdependence of supply chains and trade to gain political leverage, there are structural limits to the degree of diversification in the short to mid-term. [ABSTRACT FROM AUTHOR]

As the two largest economies in the world, the investor sentiment and stock return of China and the United States are the focus of global attention. In this paper, we study the dynamic spillover effects of investor sentiment and return between China and the United States. First, we use the relative price differences of 9 dual-listed companies in China and the United States simultaneously to verify whether investor sentiment affects stock returns. We find a significant positive correlation between the relative price difference of dual-listed companies and the difference of investor sentiment, indicating that the investor sentiment index indeed affects stock prices. Next, we construct the TVP-VAR model to study the dynamic spillover effects of investor sentiment and the return between China and the United States. Through the time-varying impulse response, we find investor sentiment has a significant dynamic impact on returns. Therefore, investment sentiment contagion and stock market linkage between China and the United States are obvious. In addition, we conduct various robust tests, and all results are consistent. [ABSTRACT FROM AUTHOR]

Probabilistic load forecasting (PLF) aims to predict the future uncertainties of loads to reduce the potential risks in power system planning and operation. In the increasingly complex power market environment, exploring advanced approaches to obtain more accurate PLF is still a significant topic. Optimizing individual forecasting method is no longer the only direction to improve the accuracy of load forecasting in recent years. Researchers started to focus on combination methods because of their better accuracy in most cases than a single model. There are existing combination methods designed for parametric environment, where some results are based on the certain assumption (e.g., Gaussian distribution assumption of single prediction). Combining probabilistic forecasts in nonparametric environment is rarely investigated, because modeling the combination problem without assuming distributions of parameters is hard. This paper proposes a novel combined model for probabilistic forecasting tailored to nonparametric environments, which combines multiple quantile-based models by minimizing the overall loss function composed of continuous ranked probability score (CRPS) under kernel density estimation (KDE). We define a multilayer Gaussian mixture distribution, which is an extended form of Gaussian mixture distribution that can simulate any distribution type in nonparametric environment. Based on the multilayer Gaussian mixture distribution, the combined model is further formulated into a quadratic programming problem with linear restrictions that can be solved efficiently. Case studies are performed using benchmark and competition datasets from the United States and China. The results show that our proposed method outperforms the best individual model and other existing combination methods. In summary, this paper constructs a complete theoretical framework of nonparametric probabilistic combination forecasting and proves its effectiveness in practical application. • Exploit an ensemble framework to combine multiple quantile forecasts. • Design a novel combined model to determine the optimal weights of base models. • Cast the combined model to a quadratic programming problem with the help of KDE. • Overcome the limitation of distribution assumption on predicted results. • Conduct case studies on ten datasets to verify the performance of the combined model. [ABSTRACT FROM AUTHOR]

The Agenda 2030 poses critical elements regarding the transition towards a more sustainable development. This paper aims at exploring and comparing the path of sustainable development within the United States and China at the subnational level. An index of Integrated Sustainable Development is introduced to measure local sustainable development on an internationally-comparable scale. This Index is computed both at the national and subnational level and the resulting scores are compared within and across the two countries, also through the adoption of convergence and cluster analysis, allowing to answer four questions: Are the US and China moving towards a sustainable development agenda? Are the current achievements uniformly distributed within the two countries? Are states/provinces converging towards a more uniform level of sustainable development? Do the existing differences and analogies between states and provinces give rise to common clusters across the two countries? The results lead to one robust conclusion: while the US can claim a better result in the national and subnational rankings of sustainable development, China exhibits a more balanced achievement in terms of synergies across Goals and spatial distribution. Nonetheless, both countries are characterized by subnational disparities and scarce achievements of Planet-related Goals. Policy recommendations are discussed accordingly. [ABSTRACT FROM AUTHOR]

Cities worldwide are facing a significant threat of stormwater hazards caused by the increase in extreme downpours and urbanization. Meso-level urban stormwater management focuses on alleviating the detrimental impacts of urban flooding and enhancing water resource utilization at the block or community scale, typically through 1) specific policies and management rules; 2) catchment-scale scenario simulation, optimization and evaluation; 3) the group of stormwater control measures implementation. It may effectively coordinate macro-level urban stormwater management planning and micro-level distributed stormwater control facilities. This study conducts a review of Urban Stormwater Management at Meso-level (USM-M) with a view to research publication trends, citation analysis, geographic spread and subject category, as well as content analysis, including temporal progression and research gaps. The Web of Science database and CiteSpace are used for the bibliometric analysis of 66 articles from 2006 to 2021. The results show that the number of USM-M topic articles generally has an upward trend over the years. Whilst the United States and China are leading research on this topic, the European countries have diverse local research and dense cooperation. Research foci have generally shifted from theoretical frameworks to multi-element subdivided topics and specific technical roadmaps. Moreover, the spatial layout optimization and multi-functional integration are, or will be, potential research directions in terms of enhancing stormwater utilization and co-benefits of USM-M. This systematic review concludes trends, challenges and potential approaches of USM-M, and aims to provide recommendations for researchers and policymakers on the development of a more advanced and comprehensive USM-M. • This paper aims to quantitatively and qualitatively review how Urban Stormwater Management at Meso-level (USM-M) is being studied and applied. • The question was "What are the trends, challenges and approaches of USM-M research?". • USM-M is applied at the catchment, block, community scale, and play a coordinator role between macro-level and micro-level. • Research focus has shifted from theoretical frameworks to subdivided topics and specific technical roadmaps. • Optimal spatial layout and multi-functional integration of USM-M implementation are potential directions. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) Remote sensing (RS) has unique advantages over traditional satellite RS, including convenience, high resolution, affordability and fast acquisition speed, making it widely used in many fields. To provide an overview of the development of UAV RS applications during the past decade, we screened related publications from the Web of Science core database from 2010 to 2021, built co-author networks, a discipline interaction network, a keywords timeline view, a co-citation cluster, and detected burst citations using bibliometrics and social network analysis. Our results show that: (1) The number of UAV RS publications had an increasing trend, with explosive growth in the past five years. The number of papers published by China and the United States (US) is far ahead in this field; (2) The US has currently the greatest influence in this field through the largest number of international cooperations. Cooperation is mainly concentrated in countries and institutions with a large number of publications but is not widely distributed. (3) The application of UAV RS involves multiple interdisciplinary subjects, among which "Environmental Science and Ecology" ranks first; (4) Future research trends of UAV RS are expected to be related to artificial intelligence (e.g., artificial neural networks-based research). This paper provides a scientific basis and guidance for future developments of UAV RS applications, which can help the research community to better grasp the developments of this field. [ABSTRACT FROM AUTHOR]

In recent years, emerging contaminants have been found in the wastewater, surface water, and even drinking water, which should be treated to ensure the safety of our living environment. In this study, we provide a comprehensive summary of wastewater treatment and emerging contaminants research from 1998 to 2021 by using the bibliometric analysis. This study is conducted based on the Web of Science Core Collection Database. The bibliometix R-package, VOSviewer and CiteSpace software are used for bibliometric analysis and science mapping. A dataset of 10, 605 publications has been retrieved. The analysis results show that China has produced the most publications. China and the United States have the closest cooperation. Analysis of the most cited papers reveals that the purification or removal techniques such as ozonation or membrane filtration can effectively remove pharmaceutical compounds from the water environment. We also found that the efficient detection of emerging contaminants and the optimization of removal methods are current challenges. Finally, future research directions are discussed. Co-occurrence network of keywords. [Display omitted] • 10,605 publications of wastewater treatment and emerging contaminants were analyzed. • China and the United States have the closest cooperation. • China, United States, and Spain have the most documents. • The publication published by Heberer (2002) receives the most citations. • Removal is a popular keyword in this research. [ABSTRACT FROM AUTHOR]

Phytoplankton blooms have caused many serious public safety incidents and eco-environmental problems worldwide and became a focus issue for research. Accurate and rapid monitoring of phytoplankton blooms is critical for forecasting, treating, and management. With the advantages of large spatial coverage and high temporal resolution, remote sensing has been widely used to monitor phytoplankton blooms. Numerous advances have been made in the remote sensing of phytoplankton blooms, biomass, and phenology over the past several decades. To fully understand the development history, research hotspots, and future trends of remote-sensing technology in the study of phytoplankton blooms, we conducted a comprehensive review to systematically analyze the research trends in the remote sensing of phytoplankton blooms through bibliometrics. Our findings showed that research on the use of remote-sensing technology in this field increased substantially in the past 30 years. "Oceanography," "Environmental Sciences," and "Remote Sensing" are the most popular subject categories. Remote Sensing of Environment, Journal of Geophysical Research: Oceans, and International Journal of Remote Sensing were the journals with the most published articles. The results of the analysis of international influence and cooperation showed that the United States had the greatest influence in this field and that the cooperation between China and the United States was the closest. The Chinese Academy of Sciences published the largest number of papers, reaching 542 articles. Keyword and topic analysis results showed that "phytoplankton," "chlorophyll," and "ocean" were the most frequently occurring keywords, while "eutrophication management and monitoring," "climate change," "lakes," and "remote-sensing algorithms" were the most popular research topics in recent years. Researchers are now paying increasing attention to the phenological response of phytoplankton under the conditions of climate change and the application of new remote-sensing methods. With the development of new remote-sensing technology and the expansion of phytoplankton research, future research should focus on (1) accurate observation of phytoplankton blooms; (2) the traits of phytoplankton blooms; and (3) the drivers, early warning, and management of phytoplankton blooms. In addition, we discuss the future challenges and opportunities in the use of remote sensing in phytoplankton blooms. Our review will promote a deeper and wider understanding of the field. [ABSTRACT FROM AUTHOR]

The trade conflict between China and the United States will have a complex and far-reaching impact on international trade patterns. The significant change in regional trade will not only impact the global transportation industry, but also have an important impact on international shipping carbon emissions. However, there are few studies that explore this issue. Based on the global multi-regional computable general equilibrium model, this study sets up three scenarios according to the development trend of the Sino–US trade conflict to measure the changes in global shipping carbon emissions under different trade conflict scenarios. The results show that, compared with the no trade conflict scenario, the tariff increase will reduce international trade by 0.329%–0.345%, but global international shipping carbon emissions will rebound by 0.25%–0.33%. The main reason for this result is that the trade conflict caused notable trade diversion. The direct trade between China and the United States became indirect trade that must be undertaken by "third countries", which will increase the global freight mileage by 0.23%–0.34%. This paper finds that Sino–US trade conflict will not only hinder international trade volume, but also increase the transportation distance of international trade of goods, which will have a negative impact on the control of carbon emissions from international shipping. This study will help to clarify the impact of the Sino–US trade conflict on international maritime carbon emissions and provide a new perspective to comprehensively identify the economic and environmental impacts of trade conflict. [Display omitted] • The newest carbon emission factors of different ship types in IMO 2020 are used. • A global multi-regional CGE model is used to simulate Sino-US trade war impacts. • The impacts on global trade patterns and shipping carbon emissions are analyzed. • Tariff hikes will increase global shipping carbon emissions through trade diversion. [ABSTRACT FROM AUTHOR]

Ecosystem service (ES) supply and human needs are often spatially conflicting. Although the synergy between them is crucial for global sustainability, little is known about the real human needs for ES (RHN) and their integration with actual ES supply. This study established a novel hierarchy of human needs for ES. Taking China and the United States as case studies, multiple types of actual ES supplies and multi-dimensional human needs were integrated to calculate the value of effective ecosystem service supply (EFS). The results suggested that the overall EFS in the United States is higher than that in China. There was a significant gap between the United States and China in areas with the first grade of EFS (F-EFS); the United States accounted for 68% of the total in such areas in the two countries combined. Whereas China accounted for 32%, mainly concentrated in the Yangtze River Delta urban group. China exhibited a gradually decreasing trend from the east coast to the northwest. Moreover, the F-EFS in China displayed more spatial concentration than in the United States. It was also discovered that the reason for the gap was a sharp spatial mismatch between actual ES supply and RHN in China. Nevertheless, China was specifically found to have the potential to enhance its EFS. This paper proposes some solutions to mitigate the gap and also offers guidance on the realization of Sustainable Development Goals (SDGs). [Display omitted] • A novel hierarchy of human needs for ecosystem services was proposed. • A large-scale analysis integrated actual ES supply and real human needs. • Actual ES supply embodying goods-based and non-goods-based ES flows were assessed. • The overall effective ecosystem service supply in the US was higher than in China. • A sharp spatial mismatch between ES supply and human needs was discovered in China. [ABSTRACT FROM AUTHOR]