Development Research Center (DRC; Chinese: 国务院发展研究中心 Hanyu Pinyin: Guówùyuàn Fāzhǎn Yánjiū Zhōngxīn) of the State Council of China is a public institution responsible for policy research, strategic review and consulting of issues related to the economic and social development on mainland China.It is an advisory body which recommends policies to CPC Central Committee and the State Council.
Food loss and waste (FLW) has emerged as a critical lever for enhancing food security and sustainable development, as land degradation and declining agricultural productivity increasingly undermine the resilience of global food systems. United Nations Sustainable Development Goal 12.3 (SDG 12.3) calls for halving per capita FLW by 2030. However, global progress, national disparities and national target allocation standards remain largely unclear. Here we develop a Global FLW-FSC Nutrient Flow Dataset (G-FFNFD) and an SDG 12.3 target gap index (TGI) to systematically evaluate global progress, further quantify national inequality and design four target allocation schemes based on distributive justice. We find that the global TGI reached 113.68% in 2022, far below expectations, while revealing inequality in FLW responsibility and associated resource-environment-economic losses. Among the four target allocation schemes, the sharing responsibility scheme performs best, with simulations across 23 SDG 12.3 pathways identifying the whole FSC high FLW reduction (S4.f2) and strong synergy (S8.a2) scenarios as most effective. The FLW reductions under these two scenarios are equivalent to annual global food production increases of 10.85% and 10.89%, respectively, enabling more than half of countries to achieve or approach the SDG 12.3 target (target gap < 25%). Our results suggest that high-income countries should prioritize reducing FLW at the consumption stage through dietary guideline scenario (S2), while lower-middle-income countries focus on whole food supply chain (FSC) technological innovation (S4.f2), thereby synergistically advancing progress towards SDG 12.3.
Currently,the new round of technological revolution is accelerating its breakthroughs,and scientific and technological innovation has become the main battlefield for the competition among major countries.Facing increasingly fierce international competition in science and technology,China must strengthen the orientation of original innovation in scientific research and technological development,shift from"catching up"to"keeping pace"and"taking the lead"in more fields,from innovation in terminal products to breakthroughs in key core technologies,and from integrated innovation to original innovation.In recent years,China's industrial competitiveness has significantly enhanced,mainly due to the gradual formation of advantages such as a super-large-scale market,a complete industrial chain,abundant talent resources,digital economy,and new energy,which have been transformed into new comprehensive competitive advantages,propelling China's industries towards the medium-high end of the global value chain.China's financial system,which is dominated by indirect financing,has played a significant role in the rapid expansion of industrialization and urbanization.However,as economic growth shifts from factor-driven to innovation-driven,the mismatch between financial service supply and the financing demands of science and technology innovation enterprises has become increasingly prominent,urgently requiring accelerated adaptive adjustments to the financial system.
Since urban construction shifts from incremental development to stock redevelopment, shantytown redevelopment has gradually become an important driver of urban revitalization. This paper evaluates the heterogeneous spillover effects of shantytown redevelopment on neighborhood housing prices utilizing difference-in-differences model and quantile regression model. Using polygon data from 38 shantytown redevelopment projects in Beijing between 2014 and 2020, this paper explores both positive mechanisms (environmental improvement, infrastructure enhancement, signal transmission, and economic agglomeration) and negative mechanisms (supply competition and construction disruption) that impact neighborhood housing prices, by distinguishing three shantytown types and tracking complete lifecycle from announcement to completion. The results show that: (1) Shantytown redevelopment indeed increases neighborhood housing price. (2) Redevelopment of urban villages, collective dormitories, and self-constructed dwellings increase neighborhood housing prices by an average of 44.09
