期刊：
Environmental Science and Pollution Research,2024年31(12):18448-18464 ISSN：0944-1344
通讯作者：
Xu, SC
作者机构：
[Hao, Meng-Ge; Meng, Xiao-Na; Xu, SC; Xu, Shi-Chun] China Univ Min & Technol, Sch Econ & Management, Xuzhou 221116, Peoples R China.;[Xue, Xiao-Fei] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
通讯机构：
[Xu, SC ] C;China Univ Min & Technol, Sch Econ & Management, Xuzhou 221116, Peoples R China.
关键词：
Digital economy;Zero-waste city;Waste management;Industrial structure upgrading;Green technology innovation
摘要：
The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.
作者机构：
[Liu, Rui; Liu, R; Yao, Xinjing; Wang, Yujun] Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;[Liu, Chang] Chinese Acad Med Sci, Inst Med Plant Dev, Beijing, Peoples R China.
通讯机构：
[Liu, R ; Liu, C ] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;Chinese Acad Med Sci, Inst Med Plant Dev, Beijing, Peoples R China.
摘要：
A DNA barcode is a short piece of standard DNA sequence used for species determination and discrimination. Representation of DNA barcodes is essential for DNA barcodes' applications in the transportation and recognition of biological materials. Previously, we have compared different strategies for representing the DNA barcodes. In the present study, we have developed a compression algorithm based on binary coding or Huffman coding scheme, followed by converting the binary digits into Base64 digits. The combination of this compression algorithm and the QR representation leads to the dynamic DNA QR coding algorithm (DDQR). We tested the DDQR algorithm on simulated data and real DNA barcode sequences from the commonly used plant and animal DNA barcode markers: rbcL, matK, trnH-psbA, ITS2, and COI. We compared the compression efficiency of DDQR and another state-of-the-art DNA compression algorithm GeCo3 for sequences with various base compositions and lengths. We found that DDQR had a higher compression rate than GeCo3 for DNA sequences shorter than 800 bp, which is the typical size range for DNA barcodes. We also upgraded a web server (http://www.1kmpg.cn/ddqr) that provides three functions: retrieval of DNA barcode sequences, encoding DNA barcode sequences to DDQR codes, and decoding DDQR codes to DNA barcode sequences. The DDQR algorithm and the webserver will be invaluable to applying DNA barcode technology in the food and traditional medicine industries.
摘要：
BACKGROUND: The web-based health question-and-answer (Q&A) community has become the primary and handy way for people to access health information and knowledge directly. OBJECTIVE: The objective of our study is to investigate how content-related, context-related, and user-related variables influence the answerability and popularity of health-related posts based on a user-dynamic, social network, and topic-dynamic semantic network, respectively. METHODS: Full-scale data on health consultations were acquired from the Metafilter Q&A community. These variables were designed in terms of context, content, and contributors. Negative binomial regression models were used to examine the influence of these variables on the favorite and comment counts of a health-related post. RESULTS: A total of 18,099 post records were collected from a well-known Q&A community. The findings of this study include the following. Content-related variables have a strong impact on both the answerability and popularity of posts. Notably, sentiment values were positively related to favorite counts and negatively associated with comment counts. User-related variables significantly affected the answerability and popularity of posts. Specifically, participation intensity was positively related to comment count and negatively associated with favorite count. Sociability breadth only had a significant impact on comment count. Context-related variables have a more substantial influence on the popularity of posts than on their answerability. The topic diversity variable exhibits an inverse correlation with the comment count while manifesting a positive correlation with the favorite count. Nevertheless, topic intensity has a significant effect only on favorite count. CONCLUSIONS: The research results not only reveal the factors influencing the answerability and popularity of health-related posts, which can help them obtain high-quality answers more efficiently, but also provide a theoretical basis for platform operators to enhance user engagement within health Q&A communities.
摘要：
Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H-T) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering. (C) 2016 Published by Elsevier Inc.
摘要：
Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.
