Quantitatively characterizing sandy soil structure altered by MICP using multi-level thresholding segmentation algorithm

The influences of biological,chemical,and flow processes on soil structure through microbially induced carbonate precipitation(MICP)are not yet fully understood.In this study,we use a multi-level thresholding segmentation algorithm,genetic algorithm(GA)enhanced Kapur entropy(KE)(GAE-KE),to accomplish quantitative characterization of sandy soil structure altered by MICP cementation.A sandy soil sample was treated using MICP method and scanned by the synchrotron radiation(SR)micro-CT with a resolution of 6.5 mm.After validation,tri-level thresholding segmentation using GAE-KE successfully separated the precipitated calcium carbonate crystals from sand particles and pores.The spatial distributions of porosity,pore structure parameters,and flow characteristics were calculated for quantitative characterization.The results offer pore-scale insights into the MICP treatment effect,and the quantitative understanding confirms the feasibility of the GAE-KE multi-level thresholding segmentation algorithm.

Neighborhood Effects and Political Trust: A Multi-level Analysis of Chinese Rural-to-Urban Migrants’ Trust in County Government

Massive rural-to-urban migration in China is consequential for political trust: rural-to-urban migrants have been found to hold lower levels of trust in local government than their rural peers who choose to stay in the countryside (mean 4.92 and 6.34 out of 10, respectively, p < 0.001). This article explores why migrants have a certain level of political trust in their county-level government. Using data of rural-to-urban migrants from the China Family Panel Survey, this study performs a hierarchical linear modeling (HLM) to unpack the multi-level explanatory factors of rural-to-urban migrants’ political trust. Findings show that the individual-level socio-economic characteristics and perceptions of government performance (Level-1), the neighborhood-level characteristics-the physical and social status and environment of neighborhoods (Level-2), and the objective macroeconomic performance of county-level government (Level-3), work together to explain migrants’ trust levels. These results suggest that considering the effects of neighborhood-level factors on rural-to-urban migrants’ political trust merits policy and public management attention in rapidly urbanizing countries.

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.

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.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

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.

Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

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”.

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.

Goals and Challenges of Global AI Governance and Chinese Solutions

In July 2023,United Nations(UN)Secretary-General Antonio Guterres called for the establishment of an entity agency responsible for artificial intelligence(AI)security governance,and organized an“AI High-level Advisory Committee”to explore pertinent issues,opening the prelude to global AI governance.In October 2023,Chinese President Xi Jinping put forward the Global AI Governance Initiative in his keynote address at the opening ceremony of the Third Belt and Road Forum for International Cooperation,elaborating China’s policy positions on AI governance to the international community.

Research on the Collaborative Governance of Social Responsibility in Online Audiovisual Enterprises

This paper aims to analyze the present conditions of the social responsibility ecosystem in online audiovisual enterprises in the digital age. It focuses on the governance of social responsibility in these enterprises and conducts an in-depth analysis of the problems and influencing factors related to the social responsibility aberrations of online audiovisual enterprises. Drawing upon social responsibility theory and collaborative governance theory, this research constructs a social responsibility guidance and governance system guided by the public, supported by the voluntary fulfillment of responsibilities by online audiovisual enterprises, and based on the collaborative participation of diverse stakeholders. It explores and optimizes the implementation pathways of this system, providing theoretical support and practical guidance for promoting the sustainable development of online audiovisual enterprises. Furthermore, it aims to contribute to the creation of a harmonious Internet ecosystem.

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.

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.

An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.

Transformation of French Governance Model for Oceanian Overseas Territories

The governance of France's overseas territories in Oceania has undergone a significant model transformation since the end of World War Ⅱ. In recent years, it has further highlighted its determination to pursue strategic autonomy. Through strict governance and legal mechanisms, France has promoted local autonomy and economic transformation, and has shifted the governance of these territories from colonial control to political cooperation and from predatory development to localized sustainable development. France's overseas territories in Oceania have increasingly become the fulcrum of its foreign strategy, serving the overall interests of its country and its overseas security. In recent years, France's governance policies in the region have become increasingly diversified, such as promoting economic diversification, strengthening regional security cooperation, weakening its independence tendencies, and promoting changes in the regional situation and relevant national policies.

Researching the Impact of the Quality of Village Governance on Farmers’Well-Being:From the Perspectives of Income and Occupational Differentiation

The goal of village governance is to improve the well-being of farmers,so this study aims to measure the impact the quality of village governance on the well-being of farmers.It also examines the heterogeneity of this impact across different farmer groups from the perspectives of income levels and occupational differentiation.To this end,this study developed an indicator system based on survey data collected from 1,442 farmers in the Sichuan,Shaanxi,and Gansu provinces,as well as the Ningxia Hui autonomous region.Multiple linear regression models were then used to analyze this data,and the findings revealed that improvements in the quality of village governance significantly increased the well-being of farmers.Specifically,primary-level empowerment and capacity building were shown to contribute the most to the enhancement of the farmers’well-being,followed by social inclusion,and social cohesion was found to have only a minimal effect.In terms of income levels,improving the quality of village governance benefited middle-income farmers the most,followed by low-income farmers,and it had the least effect on high-income farmers.In terms of occupations,full-time farmers gained the most from improvements in the quality of village governance,followed by off-farm farmers,with part-time farmers benefiting the least.Based on these findings,this study suggests that policymakers should improve the quality of village governance to enhance the well-being of farmers,focusing on the impact that level of income and occupational differentiation have on village governance.

Regarding the Regulatory Sandbox Route and Mechanism for Governance of Artificial Intelligence

The main challenge in AI governance today is striking a balance between controlling AI dangers and fostering AI innovation.Regulators in a number of nations have progressively extended the regulatory sandbox,which was first implemented in the banking sector,to AI governance in an effort to reduce the conflict between regulation and innovation.The AI regulatory sandbox is a new and feasible route for AI governance in China that not only helps to manage the risks of technology application but also prevents inhibiting AI innovation.It keeps inventors'trial-and-error tolerance space inside the regulatory purview while offering a controlled setting for the development and testing of novel AI that hasn't yet been put on the market.By providing full-cycle governance of AI with the principles of agility and inclusive prudence,the regulatory sandbox offers an alternative to the conventional top-down hard regulation,expost regulation,and tight regulation.However,the current system also has inherent limitations and practical obstacles that need to be overcome by a more rational and effective approach.To achieve its positive impact on AI governance,the AI regulatory sandbox system should build and improve the access and exit mechanism,the coordination mechanism between the sandbox and personal information protection,and the mechanisms of exemption,disclosure,and communication.

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.

Rights Risks of Using Affective Computing Technology in Public Governance and Their Regulation

As the frontier of intelligent computing technology,affective computing has been used in border inspection,case investigation,crime assessment,public opinion management,traffic management and other scenarios of public governance.However,there are still public risks associated with its failure to meet the basic requirements of modern public governance,and these risks are rooted in its technical characteristics.The technical characteristics of turning emotions into signals can give rise to such problems as degrading the right to informed consent,de-governance,and undermining human dignity when applied in public governance,and consequently can lead to social rights anxiety.Additionally,the affective modeling characteristics of affective computing tend to incur the rights risks of insufficient algorithm accuracy,algorithmic discrimination,and algorithmic black boxes.To avoid these risks,it is necessary to adopt the dynamic consent model as the premise for applying affective computing in public governance,and to regulate the auxiliary application of affective computing in public governance in a hierarchical manner,to achieve a balance between the application of affective computing technology and the protection of citizens'rights and the maintenance of public ethics.

Constructing a Triangular Linkage Model of Government Audit,Social Audit,and Internal Audit to Promote High-Quality Development of Audit Services

It is a complex and important topic to study the linkage mechanism of government audit,social audit,and internal audit in the context of China’s high-quality economic development.The implementation of measures,such as establishing a sound and perfect organizational safeguard mechanism,strengthening project collaborative audit mechanism,enhancing the mechanism for utilizing audit results,and establishing an audit and rectification joint mechanism can promote the efficient operation of the audit supervision system and the high-quality development of audit services.