An empirical study on the economic linkage characteristics of Yangtze River port cities based on discrete second-order derivatives

[1] Viallet, C. M. (2015). On the algebraic structure of rational discrete dynamical systems. Journal of Physics A: Mathematical and Theoretical, 48(16), 16FT01. Search in Google Scholar

[2] Cipin, R., Pazdera, I., Prochazka, P., et al. (2015). Discrete and continuous fractional controllers. IEEE. Search in Google Scholar

[3] Darwish, H. W., Metwally, F. H., El Bayoumi, A. (2015). Discrete wavelet transform-partial least squares versus derivative ratio spectrophotometry for simultaneous determination of chlorpheniramine maleate and dexamethasone in the presence of parabens in pharmaceutical dosage form. Tropical Journal of Pharmaceutical Research, 14(5), 859-867. Search in Google Scholar

[4] Hu, X., Wang, P. (2015). Hill-type formula and Krein-type trace formula for $ S $-periodic solutions in ODEs. arXiv preprint arXiv:1504.01815. Search in Google Scholar

[5] Temur, F. (2022). The second derivative of the discrete Hardy-Littlewood maximal function. arXiv preprint arXiv:2205.03953. Search in Google Scholar

[6] Ghiyamat, A., Shafri, H. Z. M., Mahdiraji, G. A., et al. (2015). Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform. International Journal of Remote Sensing, 36(1), 318-342. Search in Google Scholar

[7] Aoues, S., Di Loreto, M., Eberard, D., Marquis-Favre, W. (2017). Hamiltonian systems discrete-time approximation: Losslessness, passivity and composability. Systems & Control Letters, 110, 9-14. Search in Google Scholar

[8] Nikitin, S. Y., Ustinov, V. D., Shishkin, S. D. (2019). Curvature of a line defined as a discrete set of points, and diffraction pattern processing for laser ektacytometry of red blood cells. Journal of Quantitative Spectroscopy and Radiative Transfer, 235, 272-277. Search in Google Scholar

[9] Cuevas-Maraver, J., Kevrekidis, P. G., Vainchtein, A., et al. (2017). Unifying perspective: solitary traveling waves as discrete breathers in Hamiltonian lattices and energy criteria for their stability. Physical Review E, 96(3), 032214. Search in Google Scholar

[10] Otárola, E., Quyen, T. N. T. (2019). A reaction coefficient identification problem for fractional diffusion. Inverse Problems, 35(4), 045010. Search in Google Scholar

[11] Weber, F., Zacher, R. (2021). The entropy method under curvature-dimension conditions in the spirit of Bakry-Émery in the discrete setting of Markov chains. Journal of Functional Analysis, 281(5), 109061. Search in Google Scholar

[12] Meng, D., Wei, G., Sun, P. (2020). Analyzing the Characteristics and Causes of Location Spatial Agglomeration of Listed Companies: An Empirical Study of China’s Yangtze River Economic Belt. Complexity, 2020, 1-14. Search in Google Scholar

[13] Yang, J., Zhang, J., Lu, J., Sun, D. (2021). The core-periphery structure in the Yangtze River Delta: An enterprise linkage perspective, 1978–2019. Complexity, 2021, 1-15. Search in Google Scholar

[14] Chen, B., Wu, C., Huang, X., Yang, X. (2020). Examining the relationship between urban land expansion and economic linkage using coupling analysis: A case study of the Yangtze River Economic Belt, China. Sustainability, 12(3), 1227. Search in Google Scholar

[15] Liu, J., Tian, Y., Huang, K., Yi, T. (2021). Spatial-temporal differentiation of the coupling coordinated development of regional energy-economy-ecology system: A case study of the Yangtze River Economic Belt. Ecological Indicators, 124, 107394. Search in Google Scholar

[16] Zhang, R., Tai, H., Cheng, K. T., et al. (2022). Analysis on evolution characteristics and dynamic mechanism of urban green innovation network: A case study of Yangtze River economic belt. Sustainability, 14(1), 297. Search in Google Scholar

[17] Wang, N., Dong, C., Xu, H., Zhuang, Y. (2020). Letting the stones speak: An interdisciplinary survey of stone collection and construction at Liangzhu City, prehistoric Lower Yangtze River. Geoarchaeology, 35(5), 625-643.. Search in Google Scholar

[18] Zhou, K., Wu, J., Fan, J., Liu, H. (2022). Drivers of regional environmental pollution load and zoning control: a case study of the Yangtze River economic Belt, China. Chinese Geographical Science, 32, 31-48. Search in Google Scholar

[19] Wu, X., Xu, Y., Chen, H. (2020). Study on the spatial pattern of an extreme heat event by remote sensing: A case study of the 2013 extreme heat event in the Yangtze River Delta, China. Sustainability, 12(11), 4415. Search in Google Scholar

[20] Zhu, J., Wei, M., Gao, S., et al. (2021). Study on the scattering mechanism of squall lines with C-Band dual polarization radar. Part I: echo characteristics and particles phase recognition. Frontiers of Earth Science, 1-15. Search in Google Scholar

[21] Wang, C., Meng, Q. (2020). Research on the sustainable synergetic development of Chinese urban economies in the context of a study of industrial agglomeration. Sustainability, 12(3), 1122. Search in Google Scholar

[22] Wu, D., Zou, C., Cao, W., Liu, L. (2018). Analysis of the ecosystem soil conservation function based on the major function-oriented zones across the Yangtze River Economic Belt, China. Sustainability, 10(10), 3425. Search in Google Scholar

[23] Chen, L., Shen, W. (2021). Spatiotemporal differentiation of urban-rural income disparity and its driving force in the Yangtze River Economic Belt during 2000-2017. Plos One, 16(2), e0245961. Search in Google Scholar

[24] Wang, M., Wang, H. (2021). Spatial distribution patterns and influencing factors of pm 2.5 pollution in the Yangtze River delta: Empirical analysis based on a gwr model. Asia-Pacific Journal of Atmospheric Sciences, 57, 63-75. Search in Google Scholar

[25] Zhang, R., Zhang, X. (2022). Spatial–Temporal differentiation and the driving mechanism of rural transformation development in the Yangtze River economic belt. Sustainability, 14(5), 2584. Search in Google Scholar

[26] Tian, Y., Sun, C. (2018). Comprehensive carrying capacity, economic growth and the sustainable development of urban areas: A case study of the Yangtze River Economic Belt. Journal of cleaner production, 195, 486-496. Search in Google Scholar

[27] Cheng, X., Shao, H., Li, Y., et al. (2019). Urban land intensive use evaluation study based on nighttime light—A case study of the Yangtze river economic belt. Sustainability, 11(3), 675. Search in Google Scholar

[28] Han, W., Zhang, Y., Cai, J., Ma, E. (2019). Does urban industrial agglomeration lead to the improvement of land use efficiency in China? An empirical study from a spatial perspective. Sustainability, 11(4), 986. Search in Google Scholar

[29] Shangguan, Z., Wang, M. Y., Huang, J., et al. (2019). Study on Social Integration Identification and Characteristics of Migrants from “Yangtze River to Huaihe River” Project: A Time-Driven Perspective. Sustainability, 12(1), 211. Search in Google Scholar

[30] Zhong, Y., Lin, A., Zhou, Z., Chen, F. (2018). Spatial pattern evolution and optimization of urban system in the Yangtze River economic belt, China, based on DMSP-OLS night light data. Sustainability, 10(10), 3782. Search in Google Scholar

[31] Su, Y., Sun, X. P., Zhao, F. (2017). Trust and its effects on the public’s perception of flood risk: a social science investigation of the middle and lower reaches of the Yangtze River. Journal of Flood Risk Management, 10(4), 487-498. Search in Google Scholar

[32] Liu, K., Qiao, Y., Zhou, Q. (2021). Spatiotemporal heterogeneity and driving force analysis of innovation output in the Yangtze river economic zone: the perspective of innovation ecosystem. Complexity, 2021, 1-16. Search in Google Scholar

[33] Shi, Z., Xu, D., Xu, L. (2021). Spatiotemporal characteristics and impact mechanism of high-quality development of cultural tourism in the Yangtze River Delta urban agglomeration. Plos one, 16(6), e0252842. Search in Google Scholar

[34] Tao, F., Hu, Y., Tang, G., Zhou, T. (2021). Long-term evolution of the suhi footprint and urban expansion based on a temperature attenuation curve in the Yangtze river delta urban agglomeration. Sustainability, 13(15), 8530. Search in Google Scholar

[35] Wang, Z., Zhao, Z., Wang, C. (2021). Random forest analysis of factors affecting urban carbon emissions in cities within the Yangtze River Economic Belt. Plos one, 16(6), e0252337. Search in Google Scholar