RKKY Interactions in Graphene Landau Levels

We study RKKY interactions for magnetic impurities on graphene in situations where the electronic spectrum is in the form of Landau levels. Two such situations are considered: non-uniformly strained graphene, and graphene in a real magnetic field. RKKY interactions are enhanced by the lowest Landau level, which is shown to form electron states binding with the spin impurities and add a strong non-perturbative contribution to pairwise impurity spin interactions when their separation $R$ no more than the magnetic length. Beyond this interactions are found to fall off as $1/R^3$ due to perturbative effects of the negative energy Landau levels. Based on these results, we develop simple mean-field theories for both systems, taking into account the fact that typically the density of states in the lowest Landau level is much smaller than the density of spin impurities. For the strain field case, we find that the system is formally ferrimagnetic, but with very small net moment due to the relatively low density of impurities binding electrons. The transition temperature is nevertheless enhanced by them. For real fields, the system forms a canted antiferromagnet if the field is not so strong as to pin the impurity spins along the field. The possibility that the system in this latter case supports a Kosterlitz-Thouless transition is discussed

Leveraging Large Models for Crafting Narrative Visualization: A Survey

Narrative visualization effectively transforms data into engaging stories, making complex information accessible to a broad audience. Large models, essential for narrative visualization, inherently facilitate this process through their superior ability to handle natural language queries and answers, generate cohesive narratives, and enhance visual communication. Inspired by previous work in narrative visualization and recent advances in large models, we synthesized potential tasks and opportunities for large models at various stages of narrative visualization. In our study, we surveyed 79 papers to explore the role of large models in automating narrative visualization creation. We propose a comprehensive pipeline that leverages large models for crafting narrative visualization, categorizing the reviewed literature into four essential phases: Data, Narration, Visualization, and Presentation. Additionally, we identify nine specific tasks where large models are applied across these stages. This study maps out the landscape of challenges and opportunities in the LM4NV process, providing insightful directions for future research and valuable guidance for scholars in the field.Comment: 20 pages,6 figures, 2 table

Muscle activity-driven green-oriented random number generation mechanism to secure WBSN wearable device communications

Wireless body sensor networks (WBSNs) mostly consist of low-cost sensor nodes and implanted devices which generally have extremely limited capability of computations and energy capabilities. Hence, traditional security protocols and privacy enhancing technologies are not applicable to the WBSNs since their computations and cryptographic primitives are normally exceedingly complicated. Nowadays, mobile wearable and wireless muscle-computer interfaces have been integrated with the WBSN sensors for various applications such as rehabilitation, sports, entertainment, and healthcare. In this paper, we propose MGRNG, a novel muscle activity-driven green-oriented random number generation mechanism which uses the human muscle activity as green energy resource to generate random numbers (RNs). The RNs can be used to enhance the privacy of wearable device communications and secure WBSNs for rehabilitation purposes. The method was tested on 10 healthy subjects as well as 5 amputee subjects with 105 segments of simultaneously recorded surface electromyography signals from their forearm muscles. The proposed MGRNG requires only one second to generate a 128-bit RN, which is much more efficient when compared to the electrocardiography-based RN generation algorithms. Experimental results show that the RNs generated from human muscle activity signals can pass the entropy test and the NIST random test and thus can be used to secure the WBSN nodes

Greening China naturally

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in AMBIO: A Journal of the Human Environment 40 (2011): 828-831, doi:10.1007/s13280-011-0150-8.China leads the world in afforestation, and is one of the few countries whose forested area is increasing. However, this massive ‘‘greening’’ effort has been less effective than expected; afforestation has sometimes produced unintended environmental, ecological, and socioeconomic consequences, and has failed to achieve the desired ecological benefits. Where afforestation has succeeded, the approach was tailored to local environmental conditions. Using the right plant species or species composition for the site and considering alternatives such as grassland restoration have been important success factors. To expand this success, government policy should shift from a forest-based approach to a results-based approach. In addition, long-term monitoring must be implemented to provide the data needed to develop a cost-effective, scientifically informed restoration policy.This work was supported by the Fundamental Research Funds for the Central Universities (HJ2010-3) and the CAS/ SAFEA International Partnership Program for Creative Research Teams of ‘‘Ecosystem Processes and Services’’

What factors are driving the rapid growth of education levels in China?

Recognizing the critical elements that promote improvement of a country's education level (here, the mean number of years of education) is a necessary prerequisite for developing policies and plans to promote the long-term development of education and the people's quality of life. By identifying the factors that constrain the development of education and the strength of each factor's influence, we aimed to provide theoretical support and practical suggestions for advancing the development of education in China and other countries. We collected data related to China's education sector from 2000 to 2019, identified the key factors driving the per capita number of years of education of Chinese nationals, quantified their degree of influence on education, and investigated the association of each factor with the per capita education in different regions using sub-regional regression and geographic and time-weighted regression models. We found that per capita GDP, education funding, and urbanization promoted educational attainment, whereas allowing the student–teacher ratio to increase decreased educational attainment. Therefore, promoting the development of education requires that the government take measures to promote economic and social development, increase the financial investment in education, and train more high-quality teachers who can work in regions that currently lack sufficient teachers. In addition, the existence of regional heterogeneity means that both central and local governments must fully account for local realities when they formulate education policies and tailor them to local conditions

Neglected negative consequences of using exports to earn foreign exchange

The rapid growth of international trade has promoted equally rapid economic development and globalization. It has also brought some problems. To earn foreign exchange from other countries, some countries have adopted export tax rebate policies and other subsidies to enhance the international competitiveness of their products. However, earning foreign exchange from exports to other countries has also caused harms that have been neglected by many economists. To describe these harms, we studied the impact of transitioning from a completely export-oriented trade strategy to a strategy that mitigates trade’s negative impacts by considering the environmental damage associated with huge export profits. Behind the booming export earnings lies a continuous loss of real domestic wealth. Importing raw materials and exporting processed products also creates large amounts of pollution and wastes, and contributes to continuous degradation of the exporter country’s environment. It also widens the development gaps between and within countries. The core goal of socioeconomic development is to improve the livelihood of the people, not to hoard other countries' currencies. Balancing international trade therefore represents a necessary foundation for sustainable international trade, and this goal is jeopardized by excessive exports that unbalance a country’s international trade. Currency can become an invisible tax imposed on its users through depreciation caused by excessive issuance of the currency. The greater a country’s foreign exchange reserves, the greater the loss of real wealth. Therefore, to promote socioeconomic development and mitigate the problems caused by an excessive emphasis on exports, we should protect and enhance the vitality of markets (e.g., by eliminating export subsidies wherever possible) to balance exports and imports

Lessons learned from China's fall into the poverty trap

Most economists and policy-makers would now agree that economic growth - in the sense of rising per capita incomes or expenditures - reduces poverty in the developing world. However, it is also true that per capita data does not adequately account for individuals who have fallen into the poverty trap, as in China: a widening gap is developing between the rich and the poor due to a disparity in income and employment opportunities, among other factors, between rural and urban residents, and this gap is not reflected in mean (per capita) parameters. The present paper illustrates how the situation in China during the current period of reform should not be forgotten when other developing countries consider the pros and cons of China's rapid development.Poverty trap Rural-urban gap Poverty China