Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-...Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.展开更多
Optical microcavities combined with different materials have inspired many kinds of functional photonic devices,such as lasers,memories,and sensors.Among them,optofluidic microbubble resonators with intrinsic micro-ch...Optical microcavities combined with different materials have inspired many kinds of functional photonic devices,such as lasers,memories,and sensors.Among them,optofluidic microbubble resonators with intrinsic micro-channels and high-quality factors(high-Q)have been considered intriguing platforms for the combination with liquid materials,such as the hydrogel and liquid crystal.Here,we demonstrate a water-infiltrated hybrid optofluidic microcavity for the precise multidimensional measurement of the external laser field.The laser power can be precisely measured based on the photo-thermal conversion,while the wavelength-resolved measurement is realized with the intrinsic absorption spectrum of water.Empowered by machine learning,the laser power and wavelength are precisely decoupled with almost all predictions falling within the 99%prediction bands.The correlation coefficient R2 of the laser power and wavelength are as high as 0.99985 and 0.99954,respectively.This work provides a new platform for high-precision multidimensional measurement of the laser field,which can be further expanded to arbitrary band laser measurement by combining different materials.展开更多
基金National Natural Science Foundation of China,No.41771157National Key Research and Development Program of China,No.2018YFB0505402+1 种基金Scientific Research Project of Beijing Education Committee,No.KM201810028014Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds,No.025185305000/192
文摘Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.
基金supported by the National Key Research and Development Program,China(Grant No.SQ2023YFB2805600)Beijing Municipal Natural Science Foundation,China(Grant No.Z210004)+3 种基金National Natural Science Foundation of China(Grant Nos.12474372 and 12474429)the Fundamental Research Funds for the Central Universities,China(Grant No.2243300003)Beijing Nova Program from Beijing Municipal Science and Technology Commission,China(Grant No.20230484433)State Key Laboratory of Information Photonics and Optical Communications,Beijing University of Posts and Telecommunications,China(Grant No.IPOC2021ZT01).
文摘Optical microcavities combined with different materials have inspired many kinds of functional photonic devices,such as lasers,memories,and sensors.Among them,optofluidic microbubble resonators with intrinsic micro-channels and high-quality factors(high-Q)have been considered intriguing platforms for the combination with liquid materials,such as the hydrogel and liquid crystal.Here,we demonstrate a water-infiltrated hybrid optofluidic microcavity for the precise multidimensional measurement of the external laser field.The laser power can be precisely measured based on the photo-thermal conversion,while the wavelength-resolved measurement is realized with the intrinsic absorption spectrum of water.Empowered by machine learning,the laser power and wavelength are precisely decoupled with almost all predictions falling within the 99%prediction bands.The correlation coefficient R2 of the laser power and wavelength are as high as 0.99985 and 0.99954,respectively.This work provides a new platform for high-precision multidimensional measurement of the laser field,which can be further expanded to arbitrary band laser measurement by combining different materials.
