Smart city construction and urban green development: empirical evidence from China.

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions.

What influence farmers' relative poverty in China: A global analysis based on statistical and interpretable machine learning methods.

Poverty eradication has always been a major challenge to global development and governance, which received widespread attention from each country. With the completion poverty alleviation task in 2020, relative poverty governance becomes an important issue to be solved in China urgently. Because of a large population, poor infrastructures, insufficient resources, and long-term uneven development raising the living standard of farmers in rural areas is critical to China's success in realizing moderate prosperity. Therefore, identifying the poor farmers, exploring the influence factors to relative poverty, and clarifying its effect mechanism in rural areas are significant for the subsequent poverty governance. Most of the previous studies adopted the method of apriori assuming the factor system and verifying the hypothesis. We innovatively constructed a relative poverty index system consistent with China's actual conditions, selecting all the possible variables that could affect relative poverty based on the existing literature, including individual characteristics, psychological endowment, and geographical environment, and rebuilt an experimental database. Then, through data processing and data analysis, the main factors influencing the relative poverty of farmers were systematically sorted out based on the machine learning method. Finally, 25 chosen influencing factors were discussed in detail. Research findings show that: 1) Machine learning algorithm is proved it could be well applied in relative poverty fields, especially XGBoost, which achieves 81.9% accuracy and the score of ROC_AUC reaches 0.819. 2) This study sheds light on many new research directions in applying machine learning for relative poverty research, besides, the paper offers an integral framework and beneficial reference for target identification using machine learning algorithms. 3) In addition, by utilizing the interpretable tools, the "black-box" of ML become transparent through PDP and SHAP explanation, it also reveals that machine learning models can readily handle the non-linear association relationship.

A study on the long-term effects and mechanisms of internet information behavior on poverty alleviation among smallholder farmers: Evidence from China.

China has historically accomplished the task of eradicating absolute poverty, however, as a result of multiple external constraints and a lack of their own endogenous motivation, there is a general lack of viability among farmers who have been lifted out of poverty, with some of those who have been lifted out of poverty at risk of returning to poverty and marginalized populations at risk of becoming poor, and there are certain challenges to the longevity and stability of the poverty eradication of smallholder farmers. In the era of rapid development of information technology, the use of Internet information has become an important way to change the information asymmetry in rural areas, narrow the urban-rural digital divide and reduce the vulnerability of poverty at present. Based on this, this paper puts forward the corresponding research hypotheses on the theoretical basis of how Internet information behavior affects the long-term effects of poverty alleviation of smallholder farmers, and this paper is based on the empirical analysis of the household survey data of 240 smallholder farmers in 3 cities and 3 counties of H Province, in an attempt to explore empirical testing of the impact of Internet information behavior on the long-term effects of poverty alleviation of smallholder farmers, and to further reveal the intrinsic mechanism of the role of the internal mechanism of the transformation between the smallholder farmers' Internet information behavior and poverty alleviation of the long-term effects of poverty alleviation. This study found that (1) Internet information usage would be positively related to the long-term poverty alleviation of smallholder farmers; (2) Among the mechanisms of Internet information usage on the long-term poverty alleviation of smallholder farmers, agricultural income opportunities, employment opportunities and entrepreneurial business opportunities have significant mediating effects; (3) Formal social support and informal social support, all play a significant positive moderating role in the process of transformation of development opportunities carried out by smallholder farmers. The findings of the study have important practical implications for accelerating the poverty alleviation effect of the Internet and achieving sustainable poverty alleviation among small farmers to promote common prosperity.

Synergistic cytotoxicity and co-autophagy inhibition in pancreatic tumor cells and cancer-associated fibroblasts by dual functional peptide-modified liposomes.

Pancreatic ductal adenocarcinoma (PDA) is a highly fatal disease with 5-year survival of ∼8.5%. Nanoplatforms such as nab-paclitaxel and nanoliposomal irinotecan demonstrate superiority and utility in treating different progressions of PDA by prolonging the median overall survival by only a few months. Due to the dense surrounding stroma and the high autophagy in pancreatic cancer, integrin ɑvß3 targeting, acid environmental sensitive, TR peptide-modified liposomal platforms loaded with combined autophagy inhibiting hydroxychloroquine (HCQ), and cytotoxic paclitaxel (PTX) were designed (TR-PTX/HCQ-Lip) to accomplish the aim of synergistically killing tumor cells while inhibiting stroma fibrosis. The results showed that TR peptide-modified liposomes (TR-Lip) have superior targeting and penetrating effects both in vitro and in vivo. TR-PTX/HCQ-Lip efficiently inhibited autophagy in pancreatic cells and surrounding cancer-associated fibroblasts. The synergistic anti-fibrosis roles were also confirmed both in vitro and in vivo, all of which contributes to the enhanced curative effects of TR-PTX/HCQ-Lip in both heterogenetic and orthotopic pancreatic cancer models. STATEMENT OF SIGNIFICANCE: Autophagy plays a significant role in pancreatic ductal adenocarcinoma, especially in activating cancer associated fibroblasts which is also related to collagen generation that promotes the formation of dense stroma, which hinder the cytotoxic drugs to target and kill cancer cells. In this study, we designed integrin ɑvß3 targeting, acid environmental sensitive liposomal platforms to co-loaded paclitaxel and the autophagy inhibitor hydroxychloroquine. The results showed that the muti-functional liposomes can target to the pancreatic tumor and efficiently kill tumor cells and inhibit stroma fibrosis, thus improve the therapeutic effect in orthotopic pancreatic cancer models.