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Criminal activities of abducting and trafficking children take place continuously despite that they are repeatedly prohibited, which bring many negative effects to families and society. No wonder and combating criminal activities of abduction and trafficking of children is of great significance to the sustainable development of human society and the protection of national rights and interests. Taking the data of the "baobeihuijia" public welfare platform as a research sample, and using GIS and social network analysis methods, the temporal and spatial evolution and formation mechanism of China's child abduction and trafficking criminal activities were explored. The results show that: (1) Timing characteristics, from 1978 to 2020, China's child trafficking criminal activities showed an inverted "V" pattern of "high incidence in the middle of the time period and low incidence at both ends", which reached a peak in 1989 and gradually declined. (2) Topological characteristics, the overall scale of the network of child abduction and trafficking activities first increased and then decreased, the network structure became increasingly loose, the intensity and accessibility of contacts decreased, and the core provinces of the network shifted from eastern provinces such as Henan and Fujian to southwestern regions such as Sichuan and Guizhou, and the market for buyers and sellers was significantly differentiated. (3) Spatial structure, criminal activities were concentrated in the southeast half of the Hu Huanyong Line, and trafficking of boys happened more ferequently prefer in the south than in the north; On the other hand, the spatial distribution pattern of criminal activities shifted significantly, with the abducted were mostly from the southwest region, and likely to be sold to the central and eastern regions. The trafficking route followed a trend from "high incidence in several places" to "frequent nationwide" then gradually shranked, the phenomenon of cross-provincial and intra-provincial trafficking coexisted; The criminal network has formed four major criminal associations, led by the Yunnan-Guangdong-Guizhou-Hebei trafficking community, and their internal ties are close, showing the regional characteristics of coexistence of geographical proximity and leapfrogging. (4) Formation mechanism, network nodes, network connections, and network communities were the three levels that affected the situation of child trafficking activities, and each level advanced sequentially, and the level is affected by multiple factors, making it fluctuating, phased, and regional.(拐卖儿童犯罪活动屡禁不绝，给家庭和社会带来诸多负效应，打击拐卖儿童犯罪活动对人类社会可持续发展和国家权益保障意义重大。以“宝贝回家”公益平台数据资料为研究样本，借助GIS空间分析与社会网络分析方法，探讨中国拐卖儿童犯罪活动网络时空演变与形成机制。结果表明：（1）在时序演变上，1978—2020年中国拐卖儿童犯罪活动呈现“中段高发、两端低发”的倒V形态势，于1989年达到峰值后逐步回落。（2）在网络拓扑上，拐卖儿童犯罪活动网络总体规模先增后降，网络结构日趋疏松、联系强度与通达性降低，网络核心由豫、闽等中东部地区向川、黔等西南地区转移，买方、卖方市场分化显著。（3）在空间演化上，犯罪活动集中于胡焕庸线东南部，拐卖男童南方高于北方；犯罪活动空间分布格局重心转移显著，拐出高值区趋向于西南地区，拐入高值区多为中东部地区；贩运路径由“数地高发”转向“全国频发”后逐渐萎缩，跨省与省内贩运现象并存；犯罪网络形成了4个以滇-粤-桂-冀贩运社团为主导的犯罪社团，内部联系紧密，呈现地理邻近性与跳跃性并存的区位特征。（4）在形成机制上，网络节点、网络联系、网络社团3个层面对拐卖儿童犯罪活动的影响逐级递进，且受多因素影响，具有波动性、阶段性和地域性特征。)

利用q-型微积分构造了一种基于q-型整数的q-型Lupas-Kantorovich算子，利用连续模研究了q-型Lupas-Kantorovich算子的逼近速度、q-型Lupas-Kantorovich算子加权逼近性质和加权统计收敛性质。