Aspirations on the Bright Side of Humanity: It is Time to Translate Aspirations Into Actions With Establishing the Government of Earth

The thesis of this paper is that the digital noosphere of the World Wide Web and its users,the borderless move of virtually all resources of the planet,and the consequent globalization of most aspects of national politics,economy,and culture,along with the increasing difficulty of controlling the related high-tech military conflicts,human-made environmental crises,and the abnormal migrations of abused people now make it inevitable to leave behind the competitive international chaos rooted in humankind’s animal past and turn to the cooperative social spirit recommended by Aristotle,Lao Tzu,Jesus,Dante,H.G.Wells,Martin Luther King Jr.,John Lennon,Nicholas Hagger,and others to finally translate their aspirations into actions via establishing the Government of Earth for the decent and free.The paper presents a five-step,15-year,~$25B plan to start this process.That this plan has nothing to do with the Godless work of secret societies,the authoritarian urges of renewed fascism or the political absurdities of Marxism-Leninism it is relayed by the envisioned Intercontinental Education System of the outlined Government of Earth to teach every child on the planet-via a new community of digitally linked extraordinary teachers-for the beauty of lifelong learning,tolerance,duty,honor,free cooperation,and artful communication for divine missions.

Influence mechanism of government subsidy on the green transformation of coal company in China

The optimization of government subsidies to enhance the efficiency of coal companies’green transformation constitutes a critical component in the pursuit of global sustainability.We investigate the influence mechanism of government subsidies on the green transformation using data from the listed coal companies in China from 2007 to 2022.According to our findings and hypothesis testing,previous government subsidies did not have a significant direct impact on coal companies’green transformation.Nevertheless,government subsidies can help coal companies transition to greener practices by promoting innovative green initiatives.Furthermore,we confirmed an indirect route:that government subsidies enable the adoption of low-carbon initiatives,which in turn could facilitate the transition of coal companies towards green practices.In addition,we discovered that the coal company’s digitization will improve this indirect route.Thus,we propose increasing the effectiveness of government subsidies in facilitating coal companies’transition to green practices by focusing on technological advancements and enhancing company digitalization.

Inter-agency government information sharing under data-driven blockchain framework

The inter-agency government information sharing(IAGIS)plays an important role in improving service and efficiency of government agencies.Currently,there is still no effective and secure way for data-driven IAGIS to fulfill dynamic demands of information sharing between government agencies.Motivated by blockchain and data mining,a data-driven framework is proposed for IAGIS in this paper.Firstly,the blockchain is used as the core to design the whole framework for monitoring and preventing leakage and abuse of government information,in order to guarantee information security.Secondly,a four-layer architecture is designed for implementing the proposed framework.Thirdly,the classical data mining algorithms PageRank and Apriori are applied to dynamically design smart contracts for information sharing,for the purposed of flexibly adjusting the information sharing strategies according to the practical demands of government agencies for public management and public service.Finally,a case study is presented to illustrate the operation of the proposed framework.

Broadband infrared imaging governed by guidedmode resonance in dielectric metasurfaces

Nonlinear metasurfaces have experienced rapid growth recently due to their potential in various applications,including infrared imaging and spectroscopy.However,due to the low conversion efficiencies of metasurfaces,several strategies have been adopted to enhance their performances,including employing resonances at signal or nonlinear emission wavelengths.This strategy results in a narrow operational band of the nonlinear metasurfaces,which has bottlenecked many applications,including nonlinear holography,image encoding,and nonlinear metalenses.Here,we overcome this issue by introducing a new nonlinear imaging platform utilizing a pump beam to enhance signal conversion through four-wave mixing(FWM),whereby the metasurface is resonant at the pump wavelength rather than the signal or nonlinear emissions.As a result,we demonstrate broadband nonlinear imaging for arbitrary objects using metasurfaces.A silicon disk-on-slab metasurface is introduced with an excitable guided-mode resonance at the pump wavelength.This enabled direct conversion of a broad IR image ranging from>1000 to 4000 nm into visible.Importantly,adopting FWM substantially reduces the dependence on high-power signal inputs or resonant features at the signal beam of nonlinear imaging by utilizing the quadratic relationship between the pump beam intensity and the signal conversion efficiency.Our results,therefore,unlock the potential for broadband infrared imaging capabilities with metasurfaces,making a promising advancement for next-generation all-optical infrared imaging techniques with chip-scale photonic devices.

Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

Research on the Evolution of Country-Level BGP Network Ecosystems in 24 Years

The global Internet is composed of more than 70,000 autonomous domain networks interconnected through the Border Gateway Protocol(BGP).Studying the ecological evolution of BGP network is of great significance for analyzing the evolution trend of the global Internet.This paper focuses on the evolution of Country-Level BGP network ecosystems in 24 years,and innovatively studies the relationship between Country-Level BGP network and economy,breaking through the limitations of traditional research that only focuses on BGP network.The results revealed that the number of global BGP networks has increased by nearly 23 times and that network interconnection has increased nearly 80 times over in 24 years.It was found that the growth of the global BGP network ecosystem has slowed overall due to major global security events,although the BGP network ecosystem in some Southeast Asian countries is developing against the trend.At the same time,there is a significant positive correlation between the BGP network ecology and the national economy in the time dimension;there is a strong positive correlation in the spatial dimension,but the trend is weakening year by year.

Central environmental protection inspection and carbon emission reduction: A tripartite evolutionary game model from the perspective of carbon neutrality

Since the carbon neutrality target was proposed,many countries have been facing severe challenges to carbon emission reduction sustainably.This study is conducted using a tripartite evolutionary game model to explore the impact of the central environmental protection inspection(CEPI)on driving carbon emission reduction,and to study what factors influence the strategic choices of each party and how they interact with each other.The research results suggest that local governments and manufacturing enterprises would choose strategies that are beneficial to carbon reduction when CEPI increases.When the initial willingness of all parties increases 20%,50%—80%,the time spent for the whole system to achieve stability decreases from 100%,60%—30%.The evolutionary result of“thorough inspection,regulation implementation,low-carbon management”is the best strategy for the tripartite evolutionary game.Moreover,the smaller the cost and the larger the benefit,the greater the likelihood of the three-party game stability strategy appears.This study has important guiding significance for other developing countries to promote carbon emission reduction by environmental policy.

Challenges and Suggestions of Ethical Review on Clinical Research Involving Brain-Computer Interfaces

Brain-computer interface(BCI)technology is rapidly advancing in medical research and application.As an emerging biomedical engineering technology,it has garnered significant attention in the clinical research of brain disease diagnosis and treatment,neurological rehabilitation,and mental health.However,BCI also raises several challenges and ethical concerns in clinical research.In this article,the authors investigate and discuss three aspects of BCI in medicine and healthcare:the state of international ethical governance,multidimensional ethical challenges pertaining to BCI in clinical research,and suggestive concerns for ethical review.Despite the great potential of frontier BCI research and development in the field of medical care,the ethical challenges induced by itself and the complexities of clinical research and brain function have put forward new special fields for ethics in BCI.To ensure"responsible innovation"in BCI research in healthcare and medicine,the creation of an ethical global governance framework and system,along with special guidelines for cutting-edge BCI research in medicine,is suggested.

Ecosystem services potential and soil conservation policies with emphasis on degraded pastures in Brazil

Different global agendas have discussed the role of soils in mitigating and reducing global problems related to climate change,food security,biodiversity and erosion,among others.With this in mind,the aim was to draw up an overview of the main soil agendas in Europe and Brazil,analysing their impact on the establishment of legal frameworks for soil use and conservation.In Brazil,pastures are seen as an important alternative for converting degraded areas into ecosystem services.To this end,a literature review was carried out using databases on the Scopus,Web of Science,Science Direct and Scielo platforms,as well as consulting documents from the European Union Missions in Horizon Europe and Brazilian legislation on the subject.In a pilot river basin,the Potential for Conservation Use(PCU)method was applied,which is used in Brazil to assess the impacts of different uses on the natural capital of soils,serving as a metric to guide public soil conservation policies.It was concluded that,on the European scene,discussions on soils have taken place in an integrated and organised way,with actions to mobilise different players in society.In Brazil,even though there are important legal frameworks,actions are still restricted and disjointed,pointing to the need for progress in soil governance.In both scenarios,there is a need for scientifically validated metrics at regional scales that can contribute to a harmonised database capable of subsidising the development of efficient public policies to advance soil conservation at a global level.

Long-term stability in protected-areas?A vision from American/New World amphibians

Protected areas(PA)have proven to be one of the best ways to conserve biodiversity against environmental changes.Amphibians are considered the most threatened group,with habitat loss due to deforestation identified as their major threat.Here,we assessed for each PA of the American continent:1)amphibian’s occurrence(Global Biodiversity Information Facility(GBIF)vs.International Union for Conservation of Nature(IUCN)data);2)temperature velocity and estimated the climate residence time,and using the latest models of the land future use;3)we estimated the changes of natural vs.modified cover in three future scenarios.Amphibian occurrence showed differences between databases,while GBIF data shows that 52%of the amphibian species occurring in the continent are in PA,based on IUCN data,85%are protected.Results from climate change show a low pace of climate velocity during the last century that is maintained in the green scenario(SSP126).However,change in temperature increases in rate in the rest of the scenarios,with scenario SSP58 showing the highest velocity of temperature change.Future estimates of residence times in PA show that lower levels as emission scenarios tend to be higher.These results are worrisome since climate lag,specifically temperature increase over the PA will probably affect amphibian communities as shown in previous studies.Changes in climate patterns have a direct—mostly negative—impact on amphibians’ability to disperse and reproduce.The results of land use change were unexpected,since the categories showed minimal changes.However,the data on urbanization changes do not seem to be reflecting the trends of other databases,which may be causing artifacts in the comparisons in the future models of land use.Further research will be necessary to evaluate the extent of similarities and differences in future projections of land use including urbanization and human population between different databases.

Enhancing transboundary natural tourism resources governance:unveiling the spatial pattern and its influencing factors

Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensive database of transboundary natural tourism resources(TNTR)through amalgamation of diverse data sources.Utilizing the Getis-Ord Gi^(*),kernel density estimation,and geographical detectors,we scrutinize the spatial patterns of TNTR,focusing on both named and unnamed entities,while exploring the influencing factors.Our findings reveal 7883 identified TNTR in China,with mountain tourism resources emerging as the predominant type.Among provinces,Hunan boasts the highest count,while Shanghai exhibits the lowest.Southern China demonstrates a pronounced clustering trend in TNTR distribution,with the spatial arrangement of biological landscapes appearing more random compared to geological and water landscapes.Western China,characterized by intricate terrain,exhibits fewer TNTR,concurrently unveiling a significant presence of unnamed natural tourism resources.Crucially,administrative segmentation influences TNTR development,generating disparities in regional goals,developmental stages and intensities,and management approaches.In response to these variations,we advocate for strengthening the naming of the unnamed transboundary tourism resources,constructing a geographic database of TNTR for government and establishing a collaborative management mechanism based on TNTR database.Our research contributes to elucidating the intricate landscape of TNTR,offering insights for tailored governance strategies in the realm of cross-provincial tourism resource management.

Research on Risk Identification and Industrial Governance of Digital Education Products Based on Data Annotation Technology

The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.

Data-Driven Modeling of Partially Observed Biological Systems

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical behavior.As an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at all.We demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden parameters.The learned DNN model serves as an accurate predictive tool for system analysis.Through a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction process.The learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

Evolution and Governance of the Structure of Marine Economic Networks in China’s Coastal Areas: Based on Sea-related A-share Listed Companies

Data on discrete,isolated attributes of the marine economy are often used in traditional marine economic research.However,as the focus of urban research shifts from internal static attributes to external dynamic linkages,the importance of marine economic net-work research is beginning to emerge.The construction of the marine economic network in China’s coastal areas is necessary to change the flow of land and sea resources and optimize regional marine economic development.Employing data from headquarters and branches of sea-related A-share listed enterprises to construct the marine economic network in China,we use social network analysis(SNA)to discuss the characteristics of its evolution as of 2010,2015,and 2020 and its governance.The following results were obtained.1)In terms of topological characteristics,the scale of the marine economic network in China’s coastal areas has accelerated and expan-ded,and the connections have become increasingly close;thus,this development has complex network characteristics.2)In terms of spatial structure,the intensity of the connection fluctuates and does not form stable development support;the group structure gradually becomes clear,but the overall pattern is fragmented;there are spatial differences in marine economic agglomeration radiation;the radi-ation effect of the eastern marine economic circle is obvious;and the polarization effect of northern and southern marine economic circles is significant.On this basis,we construct a framework for the governance of a marine economic network with the market,the government,and industry as the three governing bodies.By clarifying the driving factors and building objectives of marine economic network construction,this study aims to foster the high-quality development of China’s marine economy.

Do companies influenced by smart cities pay more attention to green governance?Mechanism and optimal spatial correlation

Smart cities are a way for China to construct an innovative and environmentally conscious nation.The paper examines the impact of smart cities on corporate green governance and provides a theoretical foundation for formulating and executing smart city policy in China.Based on panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2008 to 2020,this study constructs a multiperiod double-difference model to examine the influence of smart cities on corporate green governance.Additionally,it uses a spatial double-difference model to investigate the spatial spillover effect of smart cities on neighboring areas.The findings indicate that smart cities effectively enhance corporate green governance.Analyzing the influencing mechanisms reveals that resource allocation efficiency,technological innovation,management environmental awareness,and regional environmental enforcement efforts act as mediators.Furthermore,the study reveals that the impact of smart cities on promoting corporate green governance is more pronounced in regions with lower levels of marketization and resource-based cities.Moreover,the research explores the spatial spillover effects of smart cities,with an effective radius of approximately 350 km.The optimal spatial correlation zone for green governance of businesses in neighboring areas in relation to smart cities is within a range of 250-350 km.This is manifested by the significant promotion of green governance in neighboring area businesses facilitated by smart cities.

Is there a peer effect on corporate ESG performance?Evidence from China’s capital market

Corporate ESG performance is an important way for stakeholders to understand the corporate environment,social responsibility,and governance behavior.Under China’s implementation of the“carbon peak and carbon neutrality”dual carbon strategic background,ESG has become an important tool to promote the achievement of the“dual carbon”goals and high-quality development.How enterprises can reasonably and effectively improve their ESG performance and promote their green and sustainable development has become a major practical problem that urgently needs to be solved.Based on social learning and dynamic competition theories,this study takes Shanghai-Shenzhen A-share listed companies from 2011 to 2021 as research samples,empirically tests whether there is a peer effect in the ESG performance of listed companies in China,and examines the generation mechanism and influencing factors of the peer effect in the ESG performance of enterprises.The results show that:(i)There is an industry and regional peer effect on the ESG performance of enterprises,where the average ESG performance of other enterprises in the same industry and region,except for the focus enterprise,significantly affects the ESG performance of the focus enterprise.This core conclusion still holds true after robustness tests such as instrumental variable method,propensity score matching method,and first order difference method to eliminate endogeneity issues,replace key measurement indicators,and control for macro factors.(ii)The mechanism analysis results show that the“information learning”and“competitive pressure”mechanisms promote the peer effect of ESG performance.(iii)Further research has found that institutional investors’attention and government environmental regulations positively and significantly impact the peer effect of corporate ESG performance.(iv)Heterogeneity analysis shows that the ESG performance peer effect is more significant for large-scale,eastern,and state-owned enterprises than for small-scale,central,western,and non-state-owned enterprises.This study expands the boundaries of current ESG theory and empirical research,and the conclusions provide important policy implications for governments and enterprises.

Changes and Adjustments:The Rule of Law Response to Medical Institution Data Compliance

Medical institution data compliance is an exogenous product of the digital society,serving as a crucial means to maintain and balance the relationship between data protection and data sharing,as well as individual interests and public interests.The implementation of the Healthy China Initiative greatly benefits from its practical significance.In practice,data from medical institutions takes varied forms,including personally identifiable data collected before diagnosis and treatment,clinical medical data generated during diagnosis and treatment,medical data collected in public health management,and potential medical data generated in daily life.In the new journey of comprehensively promoting the Chinese path to modernization,it is necessary to clarify the shift from an individual-oriented to a societal-oriented value system,highlighting the reinforcing role of the trust concept.Guided by the principle of minimizing data utilization,the focus is on the new developments and changes in medical institution data in the postpandemic era.This involves a series of measures such as fulfilling the obligation of notification and consent,specifying the scope of data collection and usage,strengthening the standardized use of relevant technical measures,and establishing a sound legal responsibility system for data compliance.Through these measures,a flexible and efficient medical institution data compliance system can be constructed.

Poverty Reduction in China: Experiences and Measurement of Effects

This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provincial panel data from 2000 to 2019.According to our research,economic growth and social development are the key drivers of poverty reduction in China,but the trickle-down effect of economic growth is diminishing and marketization is having a lesser pro-poor effect.Public expenditure has failed to provide social protection and income redistribution benefits due to issues such as targeting error and elite capture.Increasing the efficiency of the poverty reduction system calls for adaptive adjustments.Finally,this study highlights China’s poverty reduction experiences and analyzes current challenges,which serve as inspiration for consolidating poverty-reduction achievements,combating relative poverty,and attaining countryside vitalization.

China's Maritime Governance:Practical Evolution and Theoretical Construction

Increasingly engaged in maritime governance,China has developed its distinct vision and gradually established a complete theoretical system surrounding it.In terms of discourse,China has proposed a collection of concepts and ideas including a maritime community with a shared future,the 2lst Century Maritime Silk Road,Blue Partnerships,and marine ecological civilization.In terms of connotations,China champions such values as lasting peace,common prosperity,openness and inclusiveness,and cleanness and beautifulness.Exteriorly and interiorly,we can observe the unique character of China's vision concerning maritime governance,which will continue to upgrade and bear fruit in future practices,boosting the development of Chinese maritime governance theories,multilateral maritime cooperation,and ocean-related international legislation.Guided by its vision,China is expected to contribute more to global maritime security and marine ecological civilization.

A Brief Introduction to Sichuan Academy of Social Sciences

Sichuan Academy of Social Sciences is the think tank for the People’s Government of Sichuan Province and the Sichuan Provincial Committee of the CPC,with full financial backing of the Party and the government.The Academy consists of 16 institutes,1 graduate school,10 departments of scientific research management services.